Jing Li

Jing 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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9 March 2018 in Journal of Cellular Biochemistry
Verified
Journal Article
Closed access
PDF file
XWXiaobin Wang
Xiaobin Wang
MZMing-Xiang Zou
Ming-Xiang Zou
JLJing Li
Jing Li
BWBing Wang
Bing Wang
QZQianshi Zhang
Qianshi Zhang
GLGuohua Lü
Guohua Lü

1 November 2018 in Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease
Verified
Journal Article
Closed access
XWXiaobin Wang
Xiaobin Wang
BWBing Wang
Bing Wang
MZMing-Xiang Zou
Ming-Xiang Zou
JLJing Li
Jing Li
GLGuo-Hua Lv
Guo-Hua Lv
CLChang Lu
Chang Lu

24 May 2017 in Journal of Cellular Biochemistry
Verified
Journal Article
Closed access
PDF file
XWXiaobin Wang
Xiaobin Wang
GLGuohua Lv
Guohua Lv
JLJing Li
Jing Li
BWBing Wang
Bing Wang
QZQianshi Zhang
Qianshi Zhang
CLChang Lu
Chang Lu

29 September 2023 in Neuro-Oncology
Verified
Journal Article
Closed access
PDF file
TZTao-Lan Zhang
Tao-Lan Zhang
CXChao Xia
Chao Xia
BZBo-Wen Zheng
Bo-Wen Zheng
HHHai-Hong Hu
Hai-Hong Hu
LJLing-Xiang Jiang
Ling-Xiang Jiang
MZMing-Xiang Zou
Ming-Xiang Zou
Background: With cancer-associated fibroblasts (CAFs) as the main cell type, the rich myxoid stromal components in chordoma tissues may likely contribute to its development and progression. Methods: Single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, bulk RNA-seq, and multiplexed quantitative immunofluorescence (QIF) were used to dissect the heterogeneity, spatial distribution, and clinical implication of CAFs in chordoma. Results: We sequenced here 72 097 single cells from 3 primary and 3 recurrent tumor samples, as well as 3 nucleus pulposus samples as controls using scRNA-seq. We identified a unique cluster of CAF in recurrent tumors that highly expressed hypoxic genes and was functionally enriched in endoplasmic reticulum stress (ERS). Pseudotime trajectory and cell communication analyses showed that this ERS-CAF subpopulation originated from normal fibroblasts and widely interacted with tumoral and immune cells. Analyzing the bulk RNA-seq data from 126 patients, we found that the ERS-CAF signature score was associated with the invasion and poor prognosis of chordoma. By integrating the results of scRNA-seq with spatial transcriptomics, we demonstrated the existence of ERS-CAF in chordoma tissues and revealed that this CAF subtype displayed the most proximity to its surrounding tumor cells. In subsequent QIF validation involving 105 additional patients, we confirmed that ERS-CAF was abundant in the chordoma microenvironment and located close to tumor cells. Furthermore, both ERS-CAF density and its distance to tumor cells were correlated with tumor malignant phenotype and adverse patient outcomes. Conclusions: These findings depict the CAF landscape for chordoma and may provide insights into the development of novel treatment approaches.

1 January 2018 in World Neurosurgery
Verified
Journal Article
Closed access
MZMing-Xiang Zou
Ming-Xiang Zou
GLGuo-Hua Lv
Guo-Hua Lv
QZQian-Shi Zhang
Qian-Shi Zhang
SWShao-Fu Wang
Shao-Fu Wang
JLJing Li
Jing Li
XWXiao-Bin Wang
Xiao-Bin Wang

22 June 2023 in International Journal of Surgery
Verified
Journal Article
Open access
ZYZhen Yang
Zhen Yang
MZMing-Xiang Zou
Ming-Xiang Zou
HNHua-Qing Niu
Hua-Qing Niu
TZTaolan Zhang
Taolan Zhang
BZBo-Wen Zheng
Bo-Wen Zheng
Background: ChatGPT, powered by the GPT model and Transformer architecture, has demonstrated remarkable performance in the domains of medicine and healthcare, providing customized and informative responses. In our study, we investigated the potential of ChatGPT in the field of neurosurgery, focusing on its applications at the patient, neurosurgery student/resident, and neurosurgeon levels. Method: The authors conducted inquiries with ChatGPT from the viewpoints of patients, neurosurgery students/residents, and neurosurgeons, covering a range of topics, such as disease diagnosis, treatment options, prognosis, rehabilitation, and patient care. The authors also explored concepts related to neurosurgery, including fundamental principles and clinical aspects, as well as tools and techniques to enhance the skills of neurosurgery students/residents. Additionally, the authors examined disease-specific medical interventions and the decision-making processes involved in clinical practice. Results: The authors received individual responses from ChatGPT, but they tended to be shallow and repetitive, lacking depth and personalization. Furthermore, ChatGPT may struggle to discern a patient's emotional state, hindering the establishment of rapport and the delivery of appropriate care. The language used in the medical field is influenced by technical and cultural factors, and biases in the training data can result in skewed or inaccurate responses. Additionally, ChatGPT's limitations include the inability to conduct physical examinations or interpret diagnostic images, potentially overlooking complex details and individual nuances in each patient's case. Moreover, its absence in the surgical setting limits its practical utility. Conclusion: Although ChatGPT is a powerful language model, it cannot substitute for the expertise and experience of trained medical professionals. It lacks the capability to perform physical examinations, make diagnoses, administer treatments, establish trust, provide emotional support, and assist in the recovery process. Moreover, the implementation of Artificial Intelligence in healthcare necessitates careful consideration of legal and ethical concerns. While recognizing the potential of ChatGPT, additional training with comprehensive data is necessary to fully maximize its capabilities.