7 results on '"Sun, Li-Yue"'
Search Results
2. A Model Based on Artificial Intelligence Algorithm for Monitoring Recurrence of HCC after Hepatectomy
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Sun, Li-Yue, Ouyang, Qing, Cen, Wen-Jian, Wang, Fang, Tang, Wen-Ting, and Shao, Jian-Yong
- Abstract
Background There is no satisfactory indicator for monitoring recurrence after resection of hepatocellular carcinoma (HCC). This retrospective study aimed to design and validate an HCC monitor recurrence (HMR) model for patients without metastasis after hepatectomy.Methods A training cohort was recruited from 1179 patients with HCC without metastasis after hepatectomy between February 2012 and December 2015. An HMR model was developed using an AdaBoost classifier algorithm. The factors included patient age, TNM staging, tumor size, and pre/postoperative dynamic variations of alpha-fetoprotein (AFP). The diagnostic efficacy of the model was evaluated based on the area under the receiver operating characteristic curves (AUCs). The model was validated using a cohort of 695 patients.Results In preoperative patients with positive or negative AFP, the AUC of the validation cohort in the HMR model was .8877, which indicated better diagnostic efficacy than that of serum AFP (AUC, .7348). The HMR model predicted recurrence earlier than computed tomography/magnetic resonance imaging did by 191.58 ± 165 days. In addition, the HMR model can predict the prognosis of patients with HCC after resection.Conclusions The HMR model established in this study is more accurate than serum AFP for monitoring recurrence after hepatectomy for HCC and can be used for real-time monitoring of the postoperative status in patients with HCC without metastasis.
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- 2023
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3. Sleep quality, anxiety and depression in advanced lung cancer: patients and caregivers
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He, Yuan, Sun, Li-Yue, Peng, Kun-Wei, Luo, Man-Jun, Deng, Ling, Tang, Tao, and You, Chang-Xuan
- Abstract
ObjectiveTo investigate the clinical implications of sleep quality, anxiety and depression in patients with advanced lung cancer (LC) and their family caregivers (FCs).MethodsA total of 98 patients with advanced LC and their FCs (n=98) were recruited from the Oncology Department in Nanfang Hospital. The Pittsburgh Sleep Quality Index (PSQI), consisting of seven components that evaluate subjective sleep quality, sleep latency, duration of sleep, sleep efficiency, sleep disturbances, sleep medication usage and daytime dysfunction, was used to assess sleep quality. Using the tool of Zung Self-rating Anxiety Scale (SAS) and Zung Self-rating Depression Scale (SDS), we tested the patients’ status of anxiety and depression, respectively.ResultsThe prevalences of poor sleep quality, anxiety and depression in patients were 56.1%, 48.9% and 56.1%, respectively, while those in FCs were 16.3%, 32.6% and 25.5%, respectively. Patients had higher PSQI, SAS and SDS scores than did FCs (p<0.05). Significant correlations were found between the patients’ and FCs’ scores of PSQI/SAS/SDS (p<0.05). Multivariate Cox regression analyses indicated that sleep disturbances in patients (HR 0.413, 95% CI 0.21 to 0.80, p=0.01) and the global PSQI score of FCs (HR 0.31, 95% CI 0.14 to 0.71, p=0.00) were independent risk factors for patients’ first-line progression-free survival (PFS). Moreover, patients’ sleep latency (HR 2.329, 95% CI 1.36 to 3.96, p=0.00) and epidermal growth factor receptor mutations (HR 1.953, 95% CI 1.12 to 3.38, p=0.01) were significant prognostic factors for their overall survival (OS).ConclusionsWe demonstrated that presence of sleep disturbances in patients with advanced LC and the global PSQI Score of their FCs may be risk predictors for patients’ poor first-line PFS. Patients’ sleep latency was a potential risk factor for their OS.
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- 2022
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4. pH-Responsive graphene oxide/poly (methacrylic acid) hybrid nanofiltration membrane performance for water treatment.
- Author
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Sun, Li-yue, Yu, De-hao, Juan, Zhao-ge, Wang, Yao, Wang, Yan-xin, Kipper, Matt J., Huang, Lin-jun, and Tang, Jian-guo
- Subjects
METHACRYLIC acid ,WATER purification ,GRAPHENE oxide ,NANOFILTRATION ,COMPOSITE membranes (Chemistry) ,DYES & dyeing - Abstract
Graphene oxide (GO) membranes have been proposed for water treatment. GO can be used to prepare membranes that remove organic molecules, such as model dyes from contaminated wastewater. In practical applications, wastewater is often acidic or alkaline. The physico-chemical properties of GO are only weakly affected by pH, and this can lead to poor membrane performance for the removal of positively charged model compounds. In this work, we used pH-responsive poly (methacrylic acid) (PMAA) to prepare GO-PMAA materials through chemical crosslinking. GO-PMAA materials with different compositions were used to prepare membranes via physical intercalation. The membranes were tested for removal of five different dyes of different sizes and valency (including those that are positively charged, negatively charged, and neutral at neutral pH). We identify a membrane composition that works well for the removal of negatively charged methyl orange and Evans blue under acidic conditions (with 73.1% and 99.7% rejection, respectively) with improved water permeance compared to membranes prepared with GO alone. In addition, we evaluated the long-term stability of the nanofiltration membrane. After continuous operation for 20 h, the rejection rate of MnB by 5p-nGOM was about 85.37%, and the water permeance relatively stable, while the rejection rate of MnB by nGOM was about 26.59%, and the water permeance changed greatly. These findings indicate that GO membranes modified with pH-responsive polymers can achieve superior performance with respect to separation, water permeance, long-term operation, and pressure resistance, compared to GO membranes. • GO-PMAA composites were prepared by chemical cross-linking method. • GO-PMAA materials with different compositions were used to prepare membranes via physical intercalation. • Preparation of pH-responsive composite membranes. • The pH-responsive composite membrane exhibited good rejection of negatively charged dyes (MO and EB) under acidic conditions. [ABSTRACT FROM AUTHOR]
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- 2023
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5. The Prognostic Value of Alpha-Fetoprotein Ratio in Patients With Resectable Alpha-Fetoprotein-Negative Hepatocellular Carcinoma
- Author
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Sun, Li-Yue, Cen, Wen-Jian, Zeng, Xin-Xin, Zhong, Yu-Yun, Deng, Ling, Yang, Jiao-Jiao, Li, Ming, and Wang, Fang
- Abstract
Purpose This study aimed to investigate the prognostic value of alpha-fetoprotein (AFP) ratio in patients with AFP-negative hepatocellular carcinoma (HCC).Patients and Methods We retrospectively analyzed 600 AFP-negative HCC patients who underwent hepatectomy. The AFP ratio was calculated as the ratio of AFP level 1 week before surgery to the level 20-40 days after hepatectomy. Immunohistochemistry assay was used to assess protein expression in HCC tissue. The primary outcome measures were overall survival (OS) and disease-free survival (DFS).Results The study found that a cutoff value of 1.6 ng/ml for AFP ratio, determined using X-tile software, was optimal for predicting prognosis. Patients with a high AFP ratio had a worse prognosis compare to those with a low AFP ratio (DFS, P= .026; OS, P= .034). Patients with a high AFP ratio had a worse prognosis compared to those with a low AFP ratio. Multivariate analysis revealed that AFP ratio >1.6, negative HepPar-1 expression, and vascular invasion were independent predictors of both DFS and OS. Vascular invasion had a higher area under the curve (AUC) than AFP ratio and HepPar-1 expression in predicting recurrence and death. The combination of AFP ratio, HepPar-1 expression, and vascular invasion provided better predictive accuracy for DFS and OS.Conclusion The AFP ratio is a potential prognostic marker for AFP-negative HCC patients after hepatectomy. Combining the analysis of AFP ratio with HepPar-1 expression and vascular invasion can enhance the accuracy of predicting prognosis in these patients.
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- 2024
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6. pH-Responsive graphene oxide/poly (methacrylic acid) hybrid nanofiltration membrane performance for water treatment
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Sun, Li-yue, Yu, De-hao, Juan, Zhao-ge, Wang, Yao, Wang, Yan-xin, Kipper, Matt J., Huang, Lin-jun, and Tang, Jian-guo
- Abstract
Graphene oxide (GO) membranes have been proposed for water treatment. GO can be used to prepare membranes that remove organic molecules, such as model dyes from contaminated wastewater. In practical applications, wastewater is often acidic or alkaline. The physico-chemical properties of GO are only weakly affected by pH, and this can lead to poor membrane performance for the removal of positively charged model compounds. In this work, we used pH-responsive poly (methacrylic acid) (PMAA) to prepare GO-PMAA materials through chemical crosslinking. GO-PMAA materials with different compositions were used to prepare membranes via physical intercalation. The membranes were tested for removal of five different dyes of different sizes and valency (including those that are positively charged, negatively charged, and neutral at neutral pH). We identify a membrane composition that works well for the removal of negatively charged methyl orange and Evans blue under acidic conditions (with 73.1% and 99.7% rejection, respectively) with improved water permeance compared to membranes prepared with GO alone. In addition, we evaluated the long-term stability of the nanofiltration membrane. After continuous operation for 20 h, the rejection rate of MnB by 5p-nGOM was about 85.37%, and the water permeance relatively stable, while the rejection rate of MnB by nGOM was about 26.59%, and the water permeance changed greatly. These findings indicate that GO membranes modified with pH-responsive polymers can achieve superior performance with respect to separation, water permeance, long-term operation, and pressure resistance, compared to GO membranes.
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- 2023
- Full Text
- View/download PDF
7. Performance improvement strategy for water treatment films: MXene and GO
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Tao, Ke-xin, Sun, Li-yue, Yu, De-hao, Jia, Chen-yu, Juan, Zhao-ge, Wang, Yao, Wang, Yan-xin, Kipper, Matt J., Huang, Lin-jun, and Tang, Jian-guo
- Abstract
[Display omitted]
- Published
- 2023
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