Maximizing stem cell yield from limited adipose tissue: A novel two-step digestion approach and future artificial intelligence-integrated perspectives

doi:10.4252/wjsc.120206

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World Journal of Stem Cells

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1948-0210

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Stem Cells. Aug 26, 2026; 18(8): 120206
Published online Aug 26, 2026. doi: 10.4252/wjsc.120206

Maximizing stem cell yield from limited adipose tissue: A novel two-step digestion approach and future artificial intelligence-integrated perspectives

Yi-Fan Wu, Xu Jiang, Jian-Guang Zhang, Wei Zhang

Yi-Fan Wu, School of Artificial Intelligence, Guangzhou University, Guangzhou 510555, Guangdong Province, China

Xu Jiang, Guangdong Eco-Engineering Polytechnic, Guangzhou 510520, Guangdong Province, China

Jian-Guang Zhang, Xiamen Institute for Food and Drug Quality Control, Xiamen 361012, Fujian Province, China

Wei Zhang, Doctoral Workstation, Guangdong Eco-Engineering Polytechnic, Guangzhou 510520, Guangdong Province, China

Co-corresponding authors: Jian-Guang Zhang and Wei Zhang.

Author contributions: Zhang JG and Zhang W contributed equally as co-corresponding authors. Zhang JG and Zhang W contributed to the conceptualization, writing, reviewing and editing; Wu YF and Zhang W participated in the conceptualization and writing of the original draft; Jiang X assisted with literature collection and manuscript revision; and all authors participated in drafting the manuscript and all have read and approved the final version of the manuscript.

AI contribution statement: We fully adhere to the journal’s policies on AI usage. DeepSeek’s role was strictly limited to language refinement (e.g., structural coherence, grammar) and did not extend to research design, analysis, or intellectual contributions.

Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.

Corresponding author: Wei Zhang, PhD, Postdoc, Doctoral Workstation, Guangdong Eco-Engineering Polytechnic, No. 297 Guangshan First Road, Tianhe District, Guangzhou 510520, Guangdong Province, China. zw0915@163.com

Received: February 24, 2026
Revised: April 8, 2026
Accepted: May 12, 2026
Published online: August 26, 2026
Processing time: 182 Days and 17.1 Hours

Core Tip

Core Tip: The residual adipose tissue typically discarded after conventional enzymatic digestion contains viable and functionally-potent regenerative cells. The second digestion step yielded stromal vascular fraction 2, which exhibited high clonogenic potential. Although promising, the study’s generalizability is limited by its small sample size and lack of donor diversity. This review critically evaluates the methodology, discusses the impact of donor variability and enzyme lots on reproducibility, and proposes an artificial-intelligence-driven framework for personalizing digestion protocols. These insights aim to accelerate the clinical adoption and optimization of this valuable technique.