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Cheng X, Hu Y, Gui G, Hu X, Zhu J, Shi B, Bu S. Roles of Pyroptosis-Related Genes in the Diagnosis and Subtype Classification of Periodontitis. J Immunol Res 2023; 2023:8757233. [PMID: 37090158 PMCID: PMC10114156 DOI: 10.1155/2023/8757233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 12/27/2022] [Accepted: 03/18/2023] [Indexed: 04/25/2023] Open
Abstract
Pyroptosis is widely involved in many diseases, including periodontitis. Nonetheless, the functions of pyroptosis-related genes (PRGs) in periodontitis are still not fully elucidated. Therefore, we aimed to investigate the role of PRGs in periodontitis. Three datasets (GSE10334, GSE16134, and GSE173078) from the Gene Expression Omnibus (GEO) were selected to analyze the differences in expression values of the PRGs between nonperiodontitis and periodontitis tissue samples using difference analysis. Following this, five hub PRGs (charged multivesicular body protein 2B, granzyme B, Z-DNA-binding protein 1, interleukin-1β, and interferon regulatory factor 1) predicting periodontitis susceptibility were screened by establishing a random forest model, and a predictive nomogram model was constructed on the basis of these genes. Decision curve analysis suggested that the PRG-based predictive nomogram model could provide clinical benefits to patients. Three distinct PRG patterns (cluster A, cluster B, and cluster C) in the periodontitis samples were revealed according to the 48 significant PRGs, and the difference in the immune cell infiltration among the three patterns was explored. We observed that all infiltrating immune cells, except type 2 T helper cells, differ significantly among the three patterns. To quantify the PRG patterns, the PRG score was calculated by principal component analysis. According to the results, cluster B had the highest PRG score, followed by cluster A and cluster C. In conclusion, PRGs significantly contribute to the development of periodontitis. Our study of PRG patterns might open up a new avenue to guide individualized treatment plans for patients with periodontitis.
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Affiliation(s)
- Xiaofan Cheng
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yifang Hu
- Department of Geriatric Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Guan Gui
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoya Hu
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Zhu
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Bowei Shi
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shoushan Bu
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Jiang K, Wu L, Yin X, Tang Q, Yin J, Zhou Z, Yu H, Yan S. Prognostic implications of necroptosis-related long noncoding RNA signatures in muscle-invasive bladder cancer. Front Genet 2022; 13:1036098. [PMID: 36531246 PMCID: PMC9755502 DOI: 10.3389/fgene.2022.1036098] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 11/15/2022] [Indexed: 09/22/2023] Open
Abstract
Background: Bladder cancer (BLCA) is the sixth most common cancer in men, with an increasing incidence of morbidity and mortality. Necroptosis is a type of programmed cell death and plays a critical role in the biological processes of bladder cancer (BLCA). However, current studies focusing on long noncoding RNA (lncRNA) and necroptosis in cancer are limited, and there is no research about necroptosis-related lncRNAs (NRLs) in BLCA. Methods: We obtained the RNA-seq data and corresponding clinical information of BLCA from The Cancer Genome Atlas (TCGA) database. The seven determined prognostic NLRs were analyzed by several methods and verified by RT-qPCR. Then, a risk signature was established based on the aforementioned prognostic NLRs. To identify it, we evaluated its prognostic value by Kaplan-Meier (K-M) survival curve and receiver operating characteristics (ROC) curve analysis. Moreover, the relationships between risk signature and clinical features, functional enrichment, immune landscape, and drug resistance were explored as well. Results: We constructed a signature based on seven defined NLRs (HMGA2-AS1, LINC02489, ETV7-AS1, EMSLR, AC005954.1, STAG3L5P-PVRIG2P-PILRB, and LINC02178). Patients in the low-risk cohort had longer survival times than those in the high-risk cohort, and the area under the ROC curve (AUC) value of risk signature was higher than other clinical variables. Functional analyses, the infiltrating level of immune cells and functions, ESTIMATE score, and immune checkpoint analysis all indicated that the high-risk group was in a relatively immune-activated state. In terms of treatments, patients in the high-risk group were more sensitive to immunotherapy, especially anti-PD1/PD-L1 immunotherapy and conventional chemotherapy. Conclusion: The novel NLR signature acts as an invaluable tool for predicting prognosis, immune microenvironment, and drug resistance in muscle-invasive bladder cancer (MIBC) patients.
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Affiliation(s)
- Kan Jiang
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Zhejiang University Cancer Center, Hangzhou, Zhejiang, China
| | - Lingyun Wu
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Zhejiang University Cancer Center, Hangzhou, Zhejiang, China
| | - Xin Yin
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Zhejiang University Cancer Center, Hangzhou, Zhejiang, China
| | - Qiuying Tang
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Zhejiang University Cancer Center, Hangzhou, Zhejiang, China
| | - Jie Yin
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Zhejiang University Cancer Center, Hangzhou, Zhejiang, China
| | - Ziyang Zhou
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Zhejiang University Cancer Center, Hangzhou, Zhejiang, China
| | - Hao Yu
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Zhejiang University Cancer Center, Hangzhou, Zhejiang, China
| | - Senxiang Yan
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Zhejiang University Cancer Center, Hangzhou, Zhejiang, China
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Turhon M, Maimaiti A, Gheyret D, Axier A, Rexiati N, Kadeer K, Su R, Wang Z, Chen X, Cheng X, Zhang Y, Aisha M. An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine learning. Front Immunol 2022; 13:1001320. [PMID: 36248807 PMCID: PMC9556730 DOI: 10.3389/fimmu.2022.1001320] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 09/12/2022] [Indexed: 11/13/2022] Open
Abstract
Background Immunogenic Cell Death (ICD) is a novel way to regulate cell death and can sufficiently activate adaptive immune responses. Its role in immunity is still emerging. However, the involvement of ICD in Intracranial Aneurysms (IA) remains unclear. This study aimed to identify biomarkers associated with ICDs and determine the relationship between them and the immune microenvironment during the onset and progression of IA Methods The IA gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in IA were identified and the effects of the ICD on immune microenvironment signatures were studied. Techniques like Lasso, Bayes, DT, FDA, GBM, NNET, RG, SVM, LR, and multivariate analysis were used to identify the ICD gene signatures in IA. A consensus clustering algorithm was used for conducting the unsupervised cluster analysis of the ICD patterns in IA. Furthermore, enrichment analysis was carried out for investigating the various immune responses and other functional pathways. Along with functional annotation, the weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network and module construction, identification of the hub gene, and co-expression analysis were also carried out. Results The above techniques were used for establishing the ICD gene signatures of HMGB1, HMGN1, IL33, BCL2, HSPA4, PANX1, TLR9, CLEC7A, and NLRP3 that could easily distinguish IA from normal samples. The unsupervised cluster analysis helped in identifying three ICD gene patterns in different datasets. Gene enrichment analysis revealed that the IA samples showed many differences in pathways such as the cytokine-cytokine receptor interaction, regulation of actin cytoskeleton, chemokine signaling pathway, NOD-like receptor signaling pathway, viral protein interaction with the cytokines and cytokine receptors, and a few other signaling pathways compared to normal samples. In addition, the three ICD modification modes showed obvious differences in their immune microenvironment and the biological function pathways. Eight ICD-regulators were identified and showed meaningful associations with IA, suggesting they could severe as potential prognostic biomarkers. Conclusions A new gene signature for IA based on ICD features was created. This signature shows that the ICD pattern and the immune microenvironment are closely related to IA and provide a basis for optimizing risk monitoring, clinical decision-making, and developing novel treatment strategies for patients with IA.
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Affiliation(s)
- Mirzat Turhon
- Department of Neurointerventional Surgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Department of Neurointerventional Surgery, Beijing Tiantan hospital, Capital Medical University, Beijing, China
| | - Aierpati Maimaiti
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Dilmurat Gheyret
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Aximujiang Axier
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Nizamidingjiang Rexiati
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Kaheerman Kadeer
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Riqing Su
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Zengliang Wang
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Xiaohong Chen
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Xiaojiang Cheng
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
- *Correspondence: Maimaitili Aisha, ; Yisen Zhang, ; Xiaojiang Cheng,
| | - Yisen Zhang
- Department of Neurointerventional Surgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Department of Neurointerventional Surgery, Beijing Tiantan hospital, Capital Medical University, Beijing, China
- *Correspondence: Maimaitili Aisha, ; Yisen Zhang, ; Xiaojiang Cheng,
| | - Maimaitili Aisha
- Department of Neurosurgery, Neurosurgery Centre, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
- *Correspondence: Maimaitili Aisha, ; Yisen Zhang, ; Xiaojiang Cheng,
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Yu J, Tang R, Li J. Identification of pyroptosis-related lncRNA signature and AC005253.1 as a pyroptosis-related oncogene in prostate cancer. Front Oncol 2022; 12:991165. [PMID: 36248980 PMCID: PMC9556775 DOI: 10.3389/fonc.2022.991165] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 08/31/2022] [Indexed: 12/03/2022] Open
Abstract
Background Pyroptosis and prostate cancer (PCa) are closely related. The role of pyroptosis-related long non-coding RNAs (lncRNAs) (PRLs) in PCa remains elusive. This study aimed to explore the relationship between PRL and PCa prognosis. Methods Gene expression and clinical signatures were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. A PRL risk prediction model was established by survival random forest analysis and least absolute shrinkage and selection operator regression. Functional enrichment, immune status, immune checkpoints, genetic mutations, and drug susceptibility analyses related to risk scores were performed by the single-sample gene set enrichment analysis, gene set variation analysis, and copy number variation analysis. PRL expression was verified in PCa cells. Cell Counting Kit-8, 5-ethynyl-2′-deoxyuridine, wound healing, transwell, and Western blotting assay were used to detect the proliferation, migration, invasion, and pyroptosis of PCa cells, respectively. Results Prognostic features based on six PRL (AC129507.1, AC005253.1, AC127502.2, AC068580.3, LIMD1-AS1, and LINC01852) were constructed, and patients in the high-score group had a worse prognosis than those in the low-score group. This feature was determined to be independent by Cox regression analysis, and the area under the curve of the 1-, 3-, and 5-year receiver operating characteristic curves in the testing cohort was 1, 0.93, and 0.92, respectively. Moreover, the external cohort validation confirmed the robustness of the PRL risk prediction model. There was a clear distinction between the immune status of the two groups. The expression of multiple immune checkpoints was also reduced in the high-score group. Gene mutation proportion in the high-score group increased, and the sensitivity to drugs increased significantly. Six PRLs were upregulated in PCa cells. Silencing of AC005253.1 inhibited cell proliferation, migration, and invasion in DU145 and PC-3 cells. Moreover, silencing of AC005253.1 promoted pyroptosis and inflammasome AIM2 expression. Conclusions Overall, we constructed a prognostic model of PCa with six PRLs and identified their expression in PCa cells. The experimental verification showed that AC005253.1 could affect the proliferation, migration, and invasion abilities of PCa cells. Meanwhile, AC005253.1 may play an important role in PCa by affecting pyroptosis through the AIM2 inflammasome. This result requires further research for verification.
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Affiliation(s)
- JiangFan Yu
- Department of Dermatology, Second Xiangya Hospital, Central South University, Changsha, China
| | - Rui Tang
- Department of Rheumatology and Immunology, Second Xiangya Hospital, Central South University, Changsha, China
| | - JinYu Li
- Department of General Surgery, Second Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: JinYu Li,
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Cao F, Hu J, Yuan H, Cao P, Cheng Y, Wang Y. Identification of pyroptosis-related subtypes, development of a prognostic model, and characterization of tumour microenvironment infiltration in gastric cancer. Front Genet 2022; 13:963565. [PMID: 35923703 PMCID: PMC9340157 DOI: 10.3389/fgene.2022.963565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 06/27/2022] [Indexed: 11/22/2022] Open
Abstract
As a new programmed death mode, pyroptosis plays an indispensable role in gastric cancer (GC) and has strong immunotherapy potential, but the specific pathogenic mechanism and antitumor function remain unclear. We comprehensively analysed the overall changes of pyroptosis-related genes (PRGs) at the genomic and epigenetic levels in 886 GC patients. We identified two molecular subtypes by consensus unsupervised clustering analysis. Then, we calculated the risk score and constructed the risk model for predicting prognostic and selected nine PRGs related genes (IL18RAP, CTLA4, SLC2A3, IL1A, KRT7,PEG10, IGFBP2, GPA33, and DES) through LASSO and COX regression analyses in the training cohorts and were verified in the test cohorts. Consequently, a highly accurate nomogram for improving the clinical applicability of the risk score was constructed. Besides, we found that multi-layer PRGs alterations were correlated with patient clinicopathological features, prognosis, immune infiltration and TME characteristics. The low risk group mainly characterized by increased microsatellite hyperinstability, tumour mutational burden and immune infiltration. The group had lower stromal cell content, higher immune cell content and lower tumour purity. Moreover, risk score was positively correlated with T regulatory cells, M1 and M2 macrophages. In addition, the risk score was significantly associated with the cancer stem cell index and chemotherapeutic drug sensitivity. This study revealed the genomic, transcriptional and TME multiomics features of PRGs and deeply explored the potential role of pyroptosis in the TME, clinicopathological features and prognosis in GC. This study provides a new immune strategy and prediction model for clinical treatment and prognosis evaluation.
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Affiliation(s)
- Feng Cao
- Department of General Surgery, The Second Hospital of Anhui Medical University, Hefei, China
| | - Jingtao Hu
- Aviation Hygiene Branch, China Eastern Airlines Co,.Ltd, Anhui Branch, Hefei, China
| | - Hongtao Yuan
- Department of General Surgery, The Second Hospital of Anhui Medical University, Hefei, China
| | - Pengwei Cao
- Hepatopancreatobiliary Surgery, Department of General Surgery, The First Hospital of Anhui Medical University, Hefei, China
| | - Yunsheng Cheng
- Department of General Surgery, The Second Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Yunsheng Cheng, ; Yong Wang,
| | - Yong Wang
- Department of General Surgery, The Second Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Yunsheng Cheng, ; Yong Wang,
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Wang Z, Liu Y, Xiao Y, Xie Y, Wang R, Zhang Y, Zhou Q, Liu L, Sun S, Xiao H, Zou Y, Yang K, Li X, Zhao M, Hu Y, Liu H. Intelligent Nanoparticles With pH-Sensitive Co-Delivery of Temozolomide and siEGFR to Ameliorate Glioma Therapy. Front Genet 2022; 13:921051. [PMID: 35903366 PMCID: PMC9315344 DOI: 10.3389/fgene.2022.921051] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 05/03/2022] [Indexed: 11/13/2022] Open
Abstract
Glioblastoma (GBM) is one of the most lethal forms of human cancer, with very few long-term survivors. In addition to surgery, chemotherapy is still an important strategy. Unfortunately, GBM chemotherapy faces two main challenges: first, in GBM, epidermal growth factor receptor (EGFR) overexpression results in chemoresistance; second, temozolomide (TMZ) lacks target specificity, which can lead to a reduction in the concentration and side effects in GBM. Nowadays, with the development of nanomedicine systems for applications in tumor therapies, increasing anticancer efficacy and reducing side effects with multi-drug delivery are huge advantages. In this study, pH-sensitive and GBM-targeting nanovesicle (Tf-PEG-PAE(SS)) was fabricated. The chemotherapy drug (TMZ) and EGFR inhibitor (EGFR-siRNA) were co-encapsulated in the nanocarrier, and their anticancer outcomes were investigated in detail. In vitro experiments have shown that the nanocarrier transports TMZ and EGFR-siRNA efficiently into U87 cells, causing a vigorous apoptotic response by silencing the proliferative EGFR gene and increasing the drug concentration of TMZ simultaneously. An experimental study in mice bearing orthotropic glioma revealed that the accumulated nanocarriers in the tumor site could inhibit the tumor growth and prolong the mice survival remarkably through the intracranial injection of Tf-PEG-PAE(SS)/TMZ@siEGFR. The drug co-delivery system could extend the blood circulation time and offer a new strategy to treat glioblastoma.
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Affiliation(s)
- Zhen Wang
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Yuyang Liu
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Yong Xiao
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Yandong Xie
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Ran Wang
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Yiding Zhang
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Qi Zhou
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Liang Liu
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Shuo Sun
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Hong Xiao
- Department of Neuro-Psychiatric Institute, The Affiliated Brain Hospital with Nanjing Medical University, Nanjing, China
| | - Yuanjie Zou
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Kun Yang
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Xiang Li
- Department of Neurosurgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Mengjie Zhao
- Department of Neuro-Psychiatric Institute, The Affiliated Brain Hospital with Nanjing Medical University, Nanjing, China
- *Correspondence: Mengjie Zhao, ; Yifang Hu, ; Hongyi Liu,
| | - Yifang Hu
- Department of Geriatric Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Mengjie Zhao, ; Yifang Hu, ; Hongyi Liu,
| | - Hongyi Liu
- Department of Neurosurgery, The Affiliated Brain Hospital with Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
- *Correspondence: Mengjie Zhao, ; Yifang Hu, ; Hongyi Liu,
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