Yiqi Su

Dr. Yiqi Su


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2024 in Bioactive Materials
Verified
Journal Article
Open access
ZHZihao He
Zihao He
HLHui Li
Hui Li
YZYuanyuan Zhang
Yuanyuan Zhang
SGShuang Gao
Shuang Gao
KLKaini Liang
Kaini Liang
JLJianhao Lin
Jianhao Lin
Nonunions and delayed unions pose significant challenges in orthopedic treatment, with current therapies often proving inadequate. Bone tissue engineering (BTE), particularly through endochondral ossification (ECO), emerges as a promising strategy for addressing critical bone defects. This study introduces mesenchymal stem cells overexpressing Exendin-4 (MSC-E4), designed to modulate bone remodeling via their autocrine and paracrine functions. We established a type I collagen (Col-I) sponge-based in vitro model that effectively recapitulates the ECO pathway. MSC-E4 demonstrated superior chondrogenic and hypertrophic differentiation and enhanced the ECO cell fate in single-cell sequencing analysis. Furthermore, MSC-E4 encapsulated in microscaffold, effectively facilitated bone regeneration in a rat calvarial defect model, underscoring its potential as a therapeutic agent for bone regeneration. Our findings advocate for MSC-E4 within a BTE framework as a novel and potent approach for treating significant bone defects, leveraging the intrinsic ECO process.

9 July 2026 in Stem Cell Research & Therapy
Verified
Journal Article
Open access
PDF file
QCQianqian Chen
Qianqian Chen
SXShichun Xu
Shichun Xu
YSYiqi Su
Yiqi Su
SXSengyang Xiao
Sengyang Xiao
QMQingchen Meng
Qingchen Meng
HLHui Li
Hui Li
Bone defects remain a significant clinical challenge due to the limited regenerative capacity. Biomaterials can offer effective therapeutic approaches to a

Verified
Journal Article
Open access
PDF file
LCLong Crunning
Long Crunning
SXSenyang Xiao
Senyang Xiao
YSYiqi Su
Yiqi Su
HLHui Li
Hui Li
JLJianhao Lin
Jianhao Lin
Dan XingDan Xing
Dan Xing
Background/Objectives: Disease count alone does not show which multimorbidity combinations diversify or persist. We examined longitudinal changes in clinically recognisable multimorbidity profiles across three national ageing cohorts. Methods: Harmonised data from the China Health and Retirement Longitudinal Study (CHARLS), the English Longitudinal Study of Ageing (ELSA), and the U.S. Health and Retirement Study (HRS) were analysed. Eight physician-diagnosed chronic conditions were encoded as binary states, and wave-to-wave transitions (four windows in CHARLS and ELSA; five in HRS) were assessed within each cohort. State-level measures characterised accumulation, branching, persistence, and stabilisation sensitivity, supplemented by sensitivity analyses, BranchScore decomposition, prevalence-adjusted enrichment, and a disease-count-preserving permutation null model. Results: The analysis included 17,142 CHARLS, 10,272 ELSA, and 22,034 HRS participants, with baseline multimorbidity of 23.7%, 41.0%, and 58.5%, respectively. Transitions are concentrated around common profiles. One- and two-condition states (hypertension, diabetes, heart disease, chronic lung disease, psychiatric or emotional disorders) showed faster accumulation and greater branching; later persistent states were dominated by cardiometabolic-musculoskeletal combinations, particularly hypertension-heart disease-arthritis and hypertension-diabetes-arthritis. Targeted stabilisation produced modest perturbations exceeding random benchmarks. Count-preserving null models showed that early branching was largely structural, whereas selected lock-in states exceeded null expectations. Conclusions: Across three ageing cohorts, multimorbidity trajectories reflected disease composition as well as count. Because branching was strongly influenced by disease-count geometry, early branching states should be interpreted as structural cohort-level features of the cumulative framework rather than inherently predictive clinical entities. Selected cardiometabolic-musculoskeletal profiles were more persistent and may help frame integrated long-term management; patient-level prediction requires outcome-based studies.