Qingxiang Li

Mr. Qingxiang Li

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

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15 January 2021 in OncoImmunology
Verified
Journal Article
Open access
QLQingxiang Li
Qingxiang Li
YLYuke Li
Yuke Li
YWYifei Wang
Yifei Wang
LXLe Xu
Le Xu
YGYuxing Guo
Yuxing Guo
CGChuan-bin Guo
Chuan-bin Guo
Recent advances in immunotherapy, as a part of the multidisciplinary therapy, has gradually gained more attention. However, only a small proportion of patients who sensitive to the therapy could gain benefits. An increasing number of studies indicate that intestinal microbiota could enhance the efficiency of cancer immunotherapy. As one of the main probiotics, Bifidobacterium plays an important role in immune regulation, which has been proved by animal research and human clinical study. But the detailed mechanism was not clearly elucidated. Here we found oral administration of Bifidobacterium breve (B. breve) lw01 could significantly inhibit tumor growth and up-regulate tumor cell apoptosis, which relied on the recruitment of tumor-infiltrating lymphocytes and dendritic cells (DCs) in tumor microenvironment, but not Lactobacillus rhamnosus (L. rhamnosus) CGMCC 1.3724 or Escherichia coli (E. coli) MG1655. In the in situ ligated intestine loop model, B. breve’s stimulation triggered the upregulated expression of DC-related chemokine CCL20 and recruited more DCs in the intestinal villi. Further study revealed the enhancement of interleukin 12 (IL-12) secretion derived from DCs is essential to B. breve’s antitumor effect, which was counteracted by the treatment of neutralizing antibody for IL-12. Meanwhile, the modulation of intestinal microbiota caused by exogenous B. breve might enhance its antitumor effect. This study provides a simple and easy way to promote antitumor immunity via B. breve.

5 January 2024 in IEEE Journal of Biomedical and Health Informatics
Verified
Journal Article
Closed access
XZXueyu Zhang
Xueyu Zhang
QLQingxiang Li
Qingxiang Li
Wei LiWei Li
Wei Li
YGYuxing Guo
Yuxing Guo
JZJianyun Zhang
Jianyun Zhang
NLNigel Lovell
Nigel Lovell
Oral squamous cell carcinoma (OSCC) has the characteristics of early regional lymph node metastasis. OSCC patients often have poor prognoses and low survival rates due to cervical lymph metastases. Therefore, it is necessary to rely on a reasonable screening method to quickly judge the cervical lymph metastastic condition of OSCC patients and develop appropriate treatment plans. In this study, the widely used pathological sections with hematoxylin-eosin (H&E) staining are taken as the target, and combined with the advantages of hyperspectral imaging technology, a novel diagnostic method for identifying OSCC lymph node metastases is proposed. The method consists of a learning stage and a decision-making stage, focusing on cancer and non-cancer nuclei, gradually completing the lesions' segmentation from coarse to fine, and achieving high accuracy. In the learning stage, the proposed feature distillation-Net (FD-Net) network is developed to segment the cancerous and non-cancerous nuclei. In the decision-making stage, the segmentation results are post-processed, and the lesions are effectively distinguished based on the prior. Experimental results demonstrate that the proposed FD-Net is very competitive in the OSCC hyperspectral medical image segmentation task. The proposed FD-Net method performs best on the seven segmentation evaluation indicators: MIoU, OA, AA, SE, CSI, GDR, and DICE. Among these seven evaluation indicators, the proposed FD-Net method is 1.75%, 1.27%, 0.35%, 1.9%, 0.88%, 4.45%, and 1.98% higher than the DeepLab V3 method, which ranks second in performance, respectively. In addition, the proposed diagnosis method of OSCC lymph node metastasis can effectively assist pathologists in disease screening and reduce the workload of pathologists. Source codes will be released at https://github.com/MrXueyuZhang/FD-Net .

23 November 2020 in Journal of Oral Microbiology
Verified
Journal Article
Open access
QLQingxiang Li
Qingxiang Li
YPYinfei Pu
Yinfei Pu
HLHan Lu
Han Lu
NZNing Zhao
Ning Zhao
YWYifei Wang
Yifei Wang
CGChuan-bin Guo
Chuan-bin Guo
Objective: Refractory infection is an important factor affecting the progression of medication-related osteonecrosis of the jaw (MRONJ) from clinical stage I to stage II/III. The aim of this study was to explore the distribution of bacteria and their association with the inflammatory pathway of stage II/III MRONJ. Materials and Methods: Nine specimens of fresh inflammation tissue, located next to the necrotic bone or sequestrum, were collected from MRONJ patients. Nine specimens from normal oral mucosa were collected from healthy patients. The 16S rRNA gene sequencing method was used to determine the distribution characteristics of the bacterial colony. The protein microarray analysis was used to detect the expression of inflammatory cytokines. Results: The average relative abundance of Bacteroidetes, Spirochaetes, Synergistetes, and Tenericutes was higher, while Proteobacteria and Actinobacteria were lower in the MRONJ group. Most pro-inflammatory cytokines were up-regulated in the MRONJ group; yet, only IFNγ, TNFα, and IL8 showed statistical differences (P < 0.05). Porphyromonas and Treponema were positively correlated with IL8, and Mogibacterium was positively correlated with IFNγ and TNFα. Conclusions: IL8/IFNγ/TNFα pro-inflammatory effect caused by Porphyromonas, Treponema, and Mogibacterium may be the leading cause of advancing MRONJ and thus may be used as a new target for infection control.

8 April 2020 in ACS Biomaterials Science & Engineering
Verified
Journal Article
Closed access
YYYong Yin
Yong Yin
QHQianli Huang
Qianli Huang
MYMinghua Yang
Minghua Yang
JXJian Xiao
Jian Xiao
Hong WuHong Wu
Hong Wu
Kun ZhouKun Zhou
Kun Zhou

11 December 2023 in International Journal of Oral Science
Verified
Journal Article
Open access
PDF file
QLQingxiang Li
Qingxiang Li
YLYuke Li
Yuke Li
QQQiao Qiao
Qiao Qiao
NZNing Zhao
Ning Zhao
YYYuanning Yang
Yuanning Yang
YGYuxing Guo
Yuxing Guo
Recent studies have suggested that long-term application of anti-angiogenic drugs may impair oral mucosal wound healing. This study investigated the effect of sunitinib on oral mucosal healing impairment in mice and the therapeutic potential of Bifidobacterium breve (B. breve). A mouse hard palate mucosal defect model was used to investigate the influence of sunitinib and/or zoledronate on wound healing. The volume and density of the bone under the mucosal defect were assessed by micro-computed tomography (micro-CT). Inflammatory factors were detected by protein microarray analysis and enzyme-linked immunosorbent assay (ELISA). The senescence and biological functions were tested in oral mucosal stem cells (OMSCs) treated with sunitinib. Ligated loop experiments were used to investigate the effect of oral B. breve. Neutralizing antibody for interleukin-10 (IL-10) was used to prove the critical role of IL-10 in the pro-healing process derived from B. breve. Results showed that sunitinib caused oral mucosal wound healing impairment in mice. In vitro, sunitinib induced cellular senescence in OMSCs and affected biological functions such as proliferation, migration, and differentiation. Oral administration of B. breve reduced oral mucosal inflammation and promoted wound healing via intestinal dendritic cells (DCs)-derived IL-10. IL-10 reversed cellular senescence caused by sunitinib in OMSCs, and IL-10 neutralizing antibody blocked the ameliorative effect of B. breve on oral mucosal wound healing under sunitinib treatment conditions. In conclusion, sunitinib induces cellular senescence in OMSCs and causes oral mucosal wound healing impairment and oral administration of B. breve could improve wound healing impairment via intestinal DCs-derived IL-10.

1 July 2021 in International Journal of Oral and Maxillofacial Surgery
Verified
Journal Article
Closed access
QLQingxiang Li
Qingxiang Li
YWY. Wang
Y. Wang
LXL. Xu
L. Xu
LWL. Wang
L. Wang
YGYuxing Guo
Yuxing Guo
CGC. Guo
C. Guo