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A novel approach for the analysis of single-cell RNA sequencing identifies TMEM14B as a novel poor prognostic marker in hepatocellular carcinoma

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SCIENTIFIC REPORTS 2023年第1期13卷 1-12页

作者： Ma, Ding Liu, shuwen he, Qinyu Kong, Lingkai Liu, Kua Xiao, Lingjun Xin, Qilei Bi, Yanyu Wu, Junhua Jiang, Chunping Nanjing Univ Natl Inst Healthcare Data Sci State Key Lab Pharmaceut Biotechnol Med SchJiangsu Key Lab Mol Med 22 Hankou Rd Nanjing 210093 Jiangsu Peoples R China Jinan Microecol Biomed Shandong Lab Shounuo City Light West BlockQingdao Rd 3716 Jinan Shandong Peoples R China Cent South Univ Xiangya Hosp 3 Dept Gastroenterol Changsha Hunan Peoples R China

A fundamental goal in cancer-associated genome sequencing is to identify the key genes. Protein-protein interactions (PPIs) play a crucially important role in this goal. here, human reference interactome (HuRI) map was generated and 64,006 PPIs involving 9094 proteins were identified. here, we developed a physical link and co-expression combinatory network construction (PLACE) method for genes of interest, which provides a rapid way to analyze genome sequencing datasets. Next, Kaplan-Meier survival analysis, CCK8 assays, scratch wound assays and Transwell assays were applied to confirm the results. In this study, we selected single-cell sequencing data from patients with hepatocellular carcinoma (HCC) in GSE149614. The PLACE method constructs a protein connection network for genes of interest, and a large fraction (80%) of the genes (screened by the PLACE method) were associated with survival. Then, PLACE discovered that transmembrane protein 14B (TMEM14B) was the most significant prognostic key gene, and target genes of TMEM14B were predicted. The TMEM14B-target gene regulatory network was constructed by PLACE. We also detected that TMEM14B-knockdown inhibited proliferation and migration. The results demonstrate that we proposed a new effective method for identifying key genes. The PLACE method can be used widely and make outstanding contributions to the tumor research field.

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Enhanced degradation of carbamazepine in water over SC-modified NiFe2S4 nanocomposites by peroxymonosulfate activation

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CheMICAL ENGINEERING JOURNAL 2022年第Part2期450卷

作者： Fan, shuwen Shang, Jiangwei Kulan, Saifuhan he, Xiaoyan Wang, Xinglei Nasen, Bate Nie, Jing Feng, Dan Cheng, Xiuwen Yili Normal Univ Coll Chem & Environm Sci Key Lab Pollutant Chem & Environm Treatment Yining 835000 Peoples R China Lanzhou Univ Key Lab Environm Pollut Predict & Control Coll Earth & Environm Sci Lanzhou 730000 Peoples R China

In this study, novel Semi-coke-modified NiFe2S4 nanocomposites with different mass ratios are successfully prepared by hydrothermal method to activate peroxymonosulfate (PMS) for the degradation of carbamazepine (CBZ) in water. The factors affecting the degradation of CBZ, such as initial solution pH, PMS and catalyst dosage, inorganic anions, and humic acid (HA) are investigated. The possible PMS activation mechanism and CBZ possible degradation pathways are also explored. The results show that the performance of SCNF-0.5/PMS (mass ratio of SC:NiFe2S4 = 1:2) is better than that of monomeric NiFe2S4 and semi-coke (SC). X-ray photoelectron spectroscopy (XPS), electron paramagnetic resonance (EPR) spectrometer, and free radical quenching experiments show that both non-radical (O-1(2) and O-v) and free radical pathways (SO4 center dot- and radical (OH)-O-center dot) may be responsible for the degradation of CBZ, but O-1(2) is dominant active species. S2- promotes the Ni2+/Ni3+, Fe2+/Fe3+ cycle to ensure the stable performance of the catalyst, and the oxygen vacancies (O-v) in the SC act synergistically with the catalyst to promote the degradation of CBZ. This study may provide new insights into the degradation of antibiotics in water by modifying stable bimetallic sulfide to activate PMS.

关键词： SC/NiFe2S4 Advanced oxidation Peroxymonosulfate Carbamazepine Singlet oxygen

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LATS2 degradation promoted fibrosis damage and rescued by vitamin K3 in lupus nephritis

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ARTHRITIS RESEARCH & TheRAPY 2024年第1期26卷 1页

作者： Cheng, Chen Yang, Hao Yang, Chan Xie, Juan Wang, Jinshen Cheng, Luping he, Jianfu Li, Honglian Yuan, Haoxing Guo, Fangfang Li, Minmin Liu, shuwen Southern Med Univ Sch Pharmaceut Sci Guangdong Prov Key Lab New Drug Screening NMPA Key Lab Drug Metab Res & Evaluat Guangzhou 510515 Peoples R China Jinan Univ Affiliated Hosp 1 Ctr Clin Lab Guangzhou 510630 Peoples R China Southern Med Univ Guangdong Prov Inst Nephrol State Key Lab Organ Failure Res Guangzhou 510515 Peoples R China Minist Educ Innovat Ctr Med Basic Res Inflammat & Immune Relat Guangzhou 510515 Peoples R China

BackgroundLupus nephritis (LN) is the most common complication of systemic lupus erythematosus (SLE). The limited treatment options for LN increase the economic burdens on patients. Because fibrotic progression leads to irreversible renal damage in LN patients and further progresses to chronic kidney disease (CKD) and the end stage of renal disease (ESRD), developing new targets to prevent LN fibrotic progression could lead to a feasible treatment strategy for LN *** this study, we examined YAP activation and LATS2 downregulation in LN kidney biopsy samples (LN: n = 8, normal: n = 2) and lupus-prone MRL/lpr mice (n = 8 for each disease stage). The function of LATS2 was further investigated by in situ injection of Ad-LATS2 into mice with LN (n = 6 mice per group). We examined the role of SIAH2-LATS2 regulation by IP-MS and co-IP, and the protective effect of the SIAH2 inhibitor was investigated in mice with *** LATS2 by an adenovirus in vivo alleviated renal fibrotic damage in mice with LN. Moreover, we found that LATS2 was degraded by a K48 ubiquitination-proteasome pathway mediated by SIAH2 and promoted YAP activation to worsen fibrosis progression in LN. The H150 region of the substrate binding domain (SBD) is an important site for SIAH2-LATS2 binding. The SIAH2-specific inhibitor vitamin K3 protected against LN-associated fibrotic damage in *** summary, we identified the SIAH2-LATS2 axis as an attractive intervention target in LN to alter the resistance to fibrosis.

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The caring experience and supportive care needs of male partners for women with gynaecologic cancer: A qualitative literature review

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JOURNAL OF CLINICAL NURSING 2020年第23-24期29卷 4469-4481页

作者： Ge, Xiaoling Tong, Huanhuan Song, Yongxia he, Hongye Li, shuwen Hong, Jingfang Wang, Wenru Anhui Med Univ Sch Nursing 81 Mei Shan Rd Hefei Anhui Peoples R China Anhui Med Univ Affiliated Hosp 1 Hefei Peoples R China Nursing Int Collaborat Res Ctr Anhui Prov Hefei Peoples R China Natl Univ Singapore Yong Loo Lin Sch Med Alice Ctr Nursing Studies Singapore Singapore

Objective To systematically review male partners' caring experience and supportive care needs when caring for women with gynaecologic cancer. Methods The PRISMA guidelines were used to conduct this systematic review. We performed a comprehensive literature search in nine databases and qualitative studies published in English or Chinese from inception to January 2020. The included papers were appraised, using the Critical Appraisal Skills Program tool for qualitative research. An inductive thematic analysis method was adopted to synthesise major findings to construct core concepts and themes. Results Eight studies were included in this review, and four overarching themes emerged the following: the negative experience of disease, the need for supportive care to cope, adapting to a new life and post-traumatic growth. Conclusions This study shows that male partners had both negative and positive experiences in the caring process, and they could adjust themselves to some extent. Their perceived supportive care needs were often neglected. Relevance to clinical practice Male partners of women with gynaecologic cancer are an under-recognised group. The couple-oriented or family-oriented supportive care programmes should be implemented to meet the supportive care needs of male partners to enhance their health and well-being.

关键词： gynaecologic cancer literature review male partner qualitative studies supportive care needs

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Structural connectivity from DTI to predict mild cognitive impairment in de novo Parkinson's disease

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NEUROIMAGE-CLINICAL 2024年 41卷 103548-103548页

作者： Huang, Xiaofei he, Qing Ruan, Xiuhang Li, Yuting Kuang, Zhanyu Wang, Mengfan Guo, Riyu Bu, shuwen Wang, Zhaoxiu Yu, Shaode Chen, Amei Wei, Xinhua South China Univ Technol Affiliated Hosp 2 Sch Med Dept Radiol Guangzhou Guangdong Peoples R China Southern Med Univ Affiliated Dongguan Hosp Dongguan Peoples Hosp Dongguan Guangdong Peoples R China Commun Univ China Sch Informat & Commun Engn Beijing Peoples R China

Background: Early detection of Parkinson's disease (PD) patients at high risk for mild cognitive impairment (MCI) can help with timely intervention. White matter structural connectivity is considered an early and sensitive indicator of neurodegenerative disease. Objectives: To investigate whether baseline white matter structural connectivity features from diffusion tensor imaging (DTI) of de novo PD patients can help predict PD-MCI conversion at an individual level using machine learning ***: We included 90 de novo PD patients who underwent DTI and 3D T1-weighted imaging. Elastic net based feature consensus ranking (ENFCR) was used with 1000 random training sets to select clinical and structural connectivity features. Linear discrimination analysis (LDA), support vector machine (SVM), K-nearest neighbor (KNN) and naive Bayes (NB) classifiers were trained based on features selected more than 500 times. The area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN) and specificity (SPE) were used to evaluate model ***: A total of 57 PD patients were classified as PD-MCI nonconverters, and 33 PD patients were classified as PD-MCI converters. The models trained with clinical data showed moderate performance (AUC range: 0.62-0.68;ACC range: 0.63-0.77;SEN range: 0.45-0.66;SPE range: 0.64-0.84). Models trained with structural connectivity (AUC range, 0.81-0.84;ACC range, 0.75-0.86;SEN range, 0.77-0.91;SPE range, 0.71-0.88) performed similar to models that were trained with both clinical and structural connectivity data (AUC range, 0.81-0.85;ACC range, 0.74-0.85;SEN range, 0.79-0.91;SPE range, 0.70-0.89).Conclusions: Baseline white matter structural connectivity from DTI is helpful in predicting future MCI conversion in de novo PD patients.

关键词： Parkinson's disease Mild cognitive impairment Structural connectivity Diffusion tensor imaging Machine learning

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Simulation and Improvements of Oceanic Circulation and Sea Ice by the Coupled Climate System Model FGOALS-f3-L

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Advances in Atmospheric Sciences 2020年第10期37卷 1133-1148页

作者： Yuyang GUO Yongqiang YU Pengfei LIN Hailong LIU Bian he Qing BAO Bo AN shuwen ZHAO and Lijuan HUA State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China Center for Ocean Mega-Science Chinese Academy of SciencesQingdao 266071China State Key Laboratory of Severe Weather(LASW) Chinese Academy of Meteorological SciencesBeijing 100081China

This study documents simulated oceanic circulations and sea ice by the coupled climate system model FGOALS-f3-L developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics,Chinese Academy of Sciences,under historical forcing from phase 6 of the Coupled Model Intercomparison Project(CMIP6).FGOALS-f3-L reproduces the fundamental features of global oceanic circulations,such as sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(MLD),vertical temperature and salinity,and meridional overturning *** are notable improvements compared with the previous version,FGOALS-s2,such as a reduction in warm SST biases near the western and eastern boundaries of oceans and salty SSS biases in the tropical western Atlantic and eastern boundaries,and a mitigation of deep MLD biases at high ***,several obvious biases *** most significant biases include cold SST biases in the northwestern Pacific(over 4°C),freshwater SSS biases and deep MLD biases in the subtropics,and temperature and salinity biases in deep ocean at high *** simulated sea ice shows a reasonable distribution but stronger seasonal cycle than *** spatial patterns of sea ice are more realistic in FGOALS-f3-L than its previous version because the latitude–longitude grid is replaced with a tripolar grid in the ocean and sea ice *** most significant biases are the overestimated sea ice and underestimated SSS in the Labrador Sea and Barents Sea,which are related to the shallower MLD and weaker vertical mixing.

关键词： CMIP6 FGOALS-f3-L historical evaluation ocean sea ice

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Web-Based and Interpretable Machine Learning Algorithms for Early Detection of High-Frequency hearing Loss Based on a Multicenter Provincial Study in China

SSRN

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SSRN 2025年

作者： Guan, shuwen Fan, Yue Qi, Yong Yan, Fangxu Huang, Haibo Xia, Xin Li, Chunhao Hu, Yaoda he, Huijing Chen, Xingming Shan, Guangliang Department of Otolaryngology-Head and Neck Surgery Peking Union Medical College Hospital Peking Union Medical College and Chinese Academy of Medical Sciences Beijing China National Internet Finance Association of China China Department of Epidemiology and Statistics Institute of Basic Medical Sciences Chinese Academy of Medical Sciences School of Basic Medicine Peking Union Medical College Beijing China State Key Laboratory of Common Mechanism Research for Major Diseases Beijing China

Background: Early identification of high-frequency hearing loss (HF-HL) is critical for timely intervention and rehabilitation. This study aimed to identify the predictive factors for HF-HL and develop an interpretable machine learning model for early ***: A multicenter, large-sample cross-sectional study was conducted, covering three provinces in China. A total of 6,968 participants aged 20-90 were enrolled, with data collected from demographics, medical history, lifestyle, and biomedical indicators. After feature selection, eight machine learning algorithms (Naive Bayes, k-Nearest Neighbors, Support Vector Machine, Logistic Regression, Random Forest, AdaBoost, XGBoost, and TabPFN). were employed to construct predictive models. The model performance was evaluated using area under the curve (AUC), Accuracy, Precision, Recall and F1-score were calculated for each model. Additionally, ROC curves were generated to provide a visual comparison of the models' performance in predicting HF-HL. A web-based calculator was developed using the XGBoost model, which demonstrated balanced performance across various metrics. Local data processing was implemented to ensure privacy ***: The best AUC and F1 score of the final HF-HL model TabPFN were 0∙871 and 0∙861. Age, education level, gender, and other risk factors were significantly associated with HF-HL. The web-based calculator showed high stability in model ***: The identified risk factors and the developed web-based calculator provide valuable insights for the early detection and personalized intervention of HF-HL, holding significant implications for primary hearing care. The application of the web-based calculator offers a convenient tool for hearing screening in community populations. © 2025, The Authors. All rights reserved.

关键词： Support vector machines

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Z-scheme heterojunction composed of Fe doped g-C3N4 and MoS2 for efficient ciprofloxacin removal in a photo-assisted peroxymonosulfate system

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SEPARATION AND PURIFICATION TECHNOLOGY 2022年 303卷

作者： Li, Xiangchen Feng, Dan he, Xiaoyan Qian, Dayi Nasen, Bate Qi, Baochuan Fan, shuwen Shang, Jiangwei Cheng, Xiuwen Yili Normal Univ Coll Chem & Environm Sci Key Lab Pollutant Chem & Environm Treatment Yining 835000 Peoples R China Lanzhou Univ Coll Earth & Environm Sci Key Lab Environm Pollut Predict & Control Lanzhou 730000 Gansu Peoples R China

herein, a series of Z-type heterojunctions FexCN@MoS2-Y were synthesized by a combination of calcination and hydrothermal methods for the removal of ciprofloxacin (CIP) by peroxymonosulfate (PMS) activation under visible light. It was optimized that Fe3CN@MoS2-4 exhibited excellent photocatalytic performance, with the degradation rate of CIP 84 % within 140 min. Besides, its rate constants were 23.74, 3.59, and 3.98 times higher than those of pure g-C3N4, Fe3CN, and MoS2, respectively. Furthermore, the Fe3CN@MoS2-4/PMS/vis system could efficiently degrade other antibiotics (enrofloxacin (ENRO), metronidazole (MNZ) and tetracycline (TC)). The quenching experiments and electron paramagnetic resonance (EPR) characterization showed that reactive substances such as 1O2, h+ and Ovs played a dominant role in this system. We deeply explore the possible mechanisms and CIP degradation pathways for the enhanced CIP degradation efficiency in the Fe3CN@MoS2-4/ PMS/vis system. Among them, the exposed Mo (IV) and Fe (II) sites on the catalyst surface accelerated the electron transfer, while the S2-therein promoted the cycling between ions, thus increasing the reaction rate. Finally, Fe3CN@MoS2-4 maintained appreciable performance even after 5 cycles. This study may provide a new approach for the development of metal-doped g-C3N4-based complexes.

关键词： MoS2 Ciprofloxacin Peroxymonosulfate Z-heterojunction

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DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense Understanding

arXiv

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arXiv 2023年

作者： Wu, Anran Xiao, Luwei Wu, Xingjiao Yang, shuwen Xu, Junjie Zhuang, Zisong Xie, Nian Jin, Cheng he, Liang East China Normal University Shanghai China Fudan University Shanghai China Huawei Noah’s Ark Lab Shenzheng China

Visually-situated languages such as charts and plots are omnipresent in real-world documents. These graphical depictions are human-readable and are often analyzed in visually-rich documents to address a variety of questions that necessitate complex reasoning and common-sense responses. Despite the growing number of datasets that aim to answer questions over charts, most only address this task in isolation, without considering the broader context of document-level question answering. Moreover, such datasets lack adequate common-sense reasoning information in their questions. In this work, we introduce a novel task named document-level chart question answering (DCQA). The goal of this task is to conduct document-level question answering, extracting charts or plots in the document via document layout analysis (DLA) first and subsequently performing chart question answering (CQA). The newly developed benchmark dataset comprises 50,010 synthetic documents integrating charts in a wide range of styles (6 styles in contrast to 3 for PlotQA and ChartQA) and includes 699,051 questions that demand a high degree of reasoning ability and common-sense understanding. Besides, we present the development of a potent question-answer generation engine that employs table data, a rich color set, and basic question templates to produce a vast array of reasoning question-answer pairs automatically. Based on DCQA, we devise an OCR-free transformer for document-level chart-oriented understanding, capable of DLA and answering complex reasoning and common-sense questions over charts in an OCR-free manner. Our DCQA dataset is expected to foster research on understanding visualizations in documents, especially for scenarios that require complex reasoning for charts in the visually-rich document. We implement and evaluate a set of baselines, and our proposed method achieves comparable results. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Hybrid nanoassembly indicating a synthetic lethality relationship induces mitotic catastrophe-mediated tumor elimination

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CheMICAL ENGINEERING JOURNAL 2024年 479卷

作者： Zheng, Shunzhe Li, Guanting Fu, shuwen Wang, Nannan Qiao, Han Li, Meng Zhang, Xuanbo Wang, Kaiyuan Sun, Wei Tian, Chutong he, Zhonggui Ouyang, Defang Sun, Bingjun Sun, Jin Shenyang Pharmaceut Univ Wuya Coll Innovat Dept Pharmaceut Shenyang Peoples R China Shenyang Pharmaceut Univ Coll Pharm Dept Pharmaceut Shenyang Peoples R China Univ Macau Inst Chinese Med Sci ICMS State Key Lab Qual Res Chinese Med Macau Peoples R China Shenyang Pharmaceut Univ Coll Med Device Dept Biomed Engn Shenyang Peoples R China

Although DNA damage-based chemotherapy has been well investigated for clinical oncology, their effectiveness is greatly hindered by the DNA damage defenses including DNA damage repair and cell cycle arrest. herein, we propose hybrid prodrug nanoassemblies using core-matched strategy and self-assembly technology to facilitate a synthetic lethal relationship between DNA damage and DNA damage defense. Hydroxycamptothecin (HCPT), a topoisomerase I inhibitor, is chosen as the DNA toxic chemotherapeutic. Norcantharidin (NCTD), a PP2A in-hibitor, serves to abrogate homologous recombination repair and G2/M cell cycle arrest initiated by HCPT. Hybrid prodrug nanoassemblies efficiently co-deliver the two drugs with notably different physicochemical properties and lay solid foundation for their synthetic lethal synergy. The developed synthetic lethal synergy potently damages DNA and successfully attenuates DNA damage defense. More intriguingly, such synthetic lethality synergy induces tumor apoptosis by the cell death mechanism of mitotic catastrophe. In both breast tumor and colon tumor mouse models, hybrid prodrug nanoassemblies remarkably suppresses tumor prolifer-ation and improves the safety of chemotherapy. Our results provide a promising strategy to potentiate DNA damage-based translational medicine.

关键词： Prodrug nanoassembly Synthetic lethality Mitotic catastrophe Cell cycle checkpoints Translational medicine

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