LIVIVO - Search results -

Search results

Result 1 - 10 of total 338

Search options

Article ; Online: Toward ordered -omics data science: Researchers on the magic of turning metagenomic chaos into image-like patterns.

Shen, Wan Xiang / Chen, Yu Zong

Patterns (New York, N.Y.)

2023 Volume 4, Issue 1, Page(s) 100673

Abstract: Wan Xiang Shen, a postdoctoral researcher at National University of Singapore, and Yu Zong Chen ...

Abstract	Wan Xiang Shen, a postdoctoral researcher at National University of Singapore, and Yu Zong Chen, the PI of the Bioinformatics and Drug Design (BIDD) group, have developed an AI pipeline for enhanced deep learning of metagenomic data. Their
Language	English
Publishing date	2023-01-13
Publishing country	United States
Document type	News
ISSN	2666-3899
ISSN (online)	2666-3899
DOI	10.1016/j.patter.2022.100673
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Targeting Ferroptosis-Elicited Inflammation Suppresses Hepatocellular Carcinoma Metastasis and Enhances Sorafenib Efficacy.

Mu, Ming / Huang, Chun-Xiang / Qu, Chuang / Li, Pei-Lin / Wu, Xiang-Ning / Yao, Wudexin / Shen, Chu / Huang, Rucheng / Wan, Chao-Chao / Jian, Zhi-Wei / Zheng, Limin / Wu, Rui-Qi / Lao, Xiang-Ming / Kuang, Dong-Ming

Cancer research

2024 Volume 84, Issue 6, Page(s) 841–854

Abstract: Triggering ferroptosis, an iron-dependent form of cell death, has recently emerged as an approach for treating cancer. A better understanding of the role and regulation of ferroptosis is needed to realize the potential of this therapeutic strategy. Here, ...

Abstract	Triggering ferroptosis, an iron-dependent form of cell death, has recently emerged as an approach for treating cancer. A better understanding of the role and regulation of ferroptosis is needed to realize the potential of this therapeutic strategy. Here, we observed extensive activation of ferroptosis in hepatoma cells and human hepatocellular carcinoma (HCC) cases. Patients with low to moderate activation of ferroptosis in tumors had the highest risk of recurrence compared to patients with no or high ferroptosis. Upon encountering ferroptotic liver cancer cells, aggregated macrophages efficiently secreted proinflammatory IL1β to trigger neutrophil-mediated sinusoidal vascular remodeling, thereby creating favorable conditions for aggressive tumor growth and lung metastasis. Mechanistically, hyaluronan fragments released by cancer cells acted via an NF-κB-dependent pathway to upregulate IL1β precursors and the NLRP3 inflammasome in macrophages, and oxidized phospholipids secreted by ferroptotic cells activated the NLRP3 inflammasome to release functional IL1β. Depleting either macrophages or neutrophils or neutralizing IL1β in vivo effectively abrogated ferroptosis-mediated liver cancer growth and lung metastasis. More importantly, the ferroptosis-elicited inflammatory cellular network served as a negative feedback mechanism that led to therapeutic resistance to sorafenib in HCC. Targeting the ferroptosis-induced inflammatory axis significantly improved the therapeutic efficacy of sorafenib in vivo. Together, this study identified a role for ferroptosis in promoting HCC by triggering a macrophage/IL1β/neutrophil/vasculature axis. Significance: Ferroptosis induces a favorable tumor microenvironment and supports liver cancer progression by stimulating an inflammatory cellular network that can be targeted to suppress metastasis and improve the efficacy of sorafenib.
MeSH term(s)	Humans ; Carcinoma, Hepatocellular/drug therapy ; Sorafenib/pharmacology ; NLR Family, Pyrin Domain-Containing 3 Protein ; Ferroptosis ; Inflammasomes ; Liver Neoplasms/drug therapy ; Inflammation/drug therapy ; Lung Neoplasms/drug therapy ; Cell Line, Tumor ; Tumor Microenvironment
Chemical Substances	Sorafenib (9ZOQ3TZI87) ; NLR Family, Pyrin Domain-Containing 3 Protein ; Inflammasomes
Language	English
Publishing date	2024-01-17
Publishing country	United States
Document type	Journal Article
ZDB-ID	1432-1
ISSN	1538-7445 ; 0008-5472
ISSN (online)	1538-7445
ISSN	0008-5472
DOI	10.1158/0008-5472.CAN-23-1796
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Uh III Zs.135/5: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article: Efficacy and safety of Wuhu oral liquid in treating acute soft tissue injuries: a multicenter, randomized, double-blind, double-dummy, parallel-controlled trial.

Zhu, Wen-Hao / Shen, Yi / Xiao, Yu / Shi, Qi / Fan, Zhao-Xiang / Feng, Yan-Qi / Wan, Hong-Bo / Qu, Bo / Zhao, Jun / Zhang, Wei-Qiang / Xu, Guo-Hui / Wu, Xue-Qun / Tang, De-Zhi

Frontiers in pharmacology

2024 Volume 15, Page(s) 1335182

Abstract: Background: ...

Abstract	Background:
Language	English
Publishing date	2024-02-23
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2587355-6
ISSN	1663-9812
ISSN	1663-9812
DOI	10.3389/fphar.2024.1335182
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Giant magnetocaloric effect in spin supersolid candidate Na

Xiang, Junsen / Zhang, Chuandi / Gao, Yuan / Schmidt, Wolfgang / Schmalzl, Karin / Wang, Chin-Wei / Li, Bo / Xi, Ning / Liu, Xin-Yang / Jin, Hai / Li, Gang / Shen, Jun / Chen, Ziyu / Qi, Yang / Wan, Yuan / Jin, Wentao / Li, Wei / Sun, Peijie / Su, Gang

Nature

2024 Volume 625, Issue 7994, Page(s) 270–275

Abstract: Supersolid, an exotic quantum state of matter that consists of particles forming an incompressible solid structure while simultaneously showing superfluidity of zero ... ...

Abstract	Supersolid, an exotic quantum state of matter that consists of particles forming an incompressible solid structure while simultaneously showing superfluidity of zero viscosity
Language	English
Publishing date	2024-01-10
Publishing country	England
Document type	Journal Article
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/s41586-023-06885-w
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 26: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MG 9: Show issues
Zs.MO 244: Show issues

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article: Alternating nitrogen feeding strategy induced aerobic granulation: Influencing conditions and mechanism.

Wan, Chunli / Li, Zhengwen / Shen, Yanggui / Liu, Xiang

Journal of environmental sciences (China)

2021 Volume 109, Page(s) 135–147

Abstract: Effective cultivation of stable aerobic granular sludge (AGS) is a crucial step in the successful application of this technology, and the formation of AGS could be facilitated by some environmental stress conditions. Four identical sequencing batch ... ...

Abstract	Effective cultivation of stable aerobic granular sludge (AGS) is a crucial step in the successful application of this technology, and the formation of AGS could be facilitated by some environmental stress conditions. Four identical sequencing batch reactors (SBRs) were established to investigate the aerobic granulation process under the same alternating ammonia nitrogen feeding strategy superimposed with different environmental conditions (inorganic carbon source, temperature, N/COD). Although various superimposed conditions induced a significant difference in the size, settling velocity, mechanic strength of AGS, mature aerobic granules could be successfully obtained in all four reactors after 70 days' operation, indicating the alternating ammonia nitrogen feeding strategy was the most critical factor for AGS formation. Based on the results of redundancy analysis, the presence of an inorganic carbon source could facilitate the cultivation of AGS with nitrification function, while the moderate temperature and fluctuant N/COD might benefit the cultivation of more stable AGS. In addition, superimposed stress conditions could result in the difference in the microbial population between four reactors, but the population diversity and abundance of microorganisms were not the determinants of AGS formation. This study provided an effective method for the cultivation of AGS by using alternating ammonia nitrogen feeding strategy.
MeSH term(s)	Aerobiosis ; Bioreactors ; Nitrogen ; Sewage ; Waste Disposal, Fluid
Chemical Substances	Sewage ; Nitrogen (N762921K75)
Language	English
Publishing date	2021-04-24
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1092300-7
ISSN	1878-7320 ; 1001-0742
ISSN (online)	1878-7320
ISSN	1001-0742
DOI	10.1016/j.jes.2021.03.044
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Bonn / Germany

Z 7630: Show issues

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Snowflake Point Deconvolution for Point Cloud Completion and Generation With Skip-Transformer.

Xiang, Peng / Wen, Xin / Liu, Yu-Shen / Cao, Yan-Pei / Wan, Pengfei / Zheng, Wen / Han, Zhizhong

IEEE transactions on pattern analysis and machine intelligence

2023 Volume 45, Issue 5, Page(s) 6320–6338

Abstract: Most existing point cloud completion methods suffer from the discrete nature of point clouds and the unstructured prediction of points in local regions, which makes it difficult to reveal fine local geometric details. To resolve this issue, we propose ... ...

Abstract	Most existing point cloud completion methods suffer from the discrete nature of point clouds and the unstructured prediction of points in local regions, which makes it difficult to reveal fine local geometric details. To resolve this issue, we propose SnowflakeNet with snowflake point deconvolution (SPD) to generate complete point clouds. SPD models the generation of point clouds as the snowflake-like growth of points, where child points are generated progressively by splitting their parent points after each SPD. Our insight into the detailed geometry is to introduce a skip-transformer in the SPD to learn the point splitting patterns that can best fit the local regions. The skip-transformer leverages attention mechanism to summarize the splitting patterns used in the previous SPD layer to produce the splitting in the current layer. The locally compact and structured point clouds generated by SPD precisely reveal the structural characteristics of the 3D shape in local patches, which enables us to predict highly detailed geometries. Moreover, since SPD is a general operation that is not limited to completion, we explore its applications in other generative tasks, including point cloud auto-encoding, generation, single image reconstruction, and upsampling. Our experimental results outperform state-of-the-art methods under widely used benchmarks.
Language	English
Publishing date	2023-04-03
Publishing country	United States
Document type	Journal Article
ISSN	1939-3539
ISSN (online)	1939-3539
DOI	10.1109/TPAMI.2022.3217161
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction.

Cheng, Kai Ping / Shen, Wan Xiang / Jiang, Yu Yang / Chen, Yan / Chen, Yu Zong / Tan, Ying

Computers in biology and medicine

2023 Volume 164, Page(s) 107245

Abstract: Clinical outcome prediction is important for stratified therapeutics. Machine learning (ML) and deep learning (DL) methods facilitate therapeutic response prediction from transcriptomic profiles of cells and clinical samples. Clinical transcriptomic DL ... ...

Abstract	Clinical outcome prediction is important for stratified therapeutics. Machine learning (ML) and deep learning (DL) methods facilitate therapeutic response prediction from transcriptomic profiles of cells and clinical samples. Clinical transcriptomic DL is challenged by the low-sample sizes (34-286 subjects), high-dimensionality (up to 21,653 genes) and unordered nature of clinical transcriptomic data. The established methods rely on ML algorithms at accuracy levels of 0.6-0.8 AUC/ACC values. Low-sample DL algorithms are needed for enhanced prediction capability. Here, an unsupervised manifold-guided algorithm was employed for restructuring transcriptomic data into ordered image-like 2D-representations, followed by efficient DL of these 2D-representations with deep ConvNets. Our DL models significantly outperformed the state-of-the-art (SOTA) ML models on 82% of 17 low-sample benchmark datasets (53% with >0.05 AUC/ACC improvement). They are more robust than the SOTA models in cross-cohort prediction tasks, and in identifying robust biomarkers and response-dependent variational patterns consistent with experimental indications.
MeSH term(s)	Humans ; Deep Learning ; Gene Expression Profiling ; Transcriptome ; Algorithms ; Benchmarking
Language	English
Publishing date	2023-07-18
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	127557-4
ISSN	1879-0534 ; 0010-4825
ISSN (online)	1879-0534
ISSN	0010-4825
DOI	10.1016/j.compbiomed.2023.107245
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 653: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article: Alternating nitrogen feeding strategy induced aerobic granulation: Influencing conditions and mechanism

Wan, Chunli / Li, Zhengwen / Shen, Yanggui / Liu, Xiang

Journal of environmental sciences (China). 2021 Nov., v. 109

2021

Abstract	Effective cultivation of stable aerobic granular sludge (AGS) is a crucial step in the successful application of this technology, and the formation of AGS could be facilitated by some environmental stress conditions. Four identical sequencing batch reactors (SBRs) were established to investigate the aerobic granulation process under the same alternating ammonia nitrogen feeding strategy superimposed with different environmental conditions (inorganic carbon source, temperature, N/COD). Although various superimposed conditions induced a significant difference in the size, settling velocity, mechanic strength of AGS, mature aerobic granules could be successfully obtained in all four reactors after 70 days' operation, indicating the alternating ammonia nitrogen feeding strategy was the most critical factor for AGS formation. Based on the results of redundancy analysis, the presence of an inorganic carbon source could facilitate the cultivation of AGS with nitrification function, while the moderate temperature and fluctuant N/COD might benefit the cultivation of more stable AGS. In addition, superimposed stress conditions could result in the difference in the microbial population between four reactors, but the population diversity and abundance of microorganisms were not the determinants of AGS formation. This study provided an effective method for the cultivation of AGS by using alternating ammonia nitrogen feeding strategy.
Keywords	ammonium nitrogen ; inorganic carbon ; nitrification ; nitrogen ; sludge ; temperature ; China
Language	English
Dates of publication	2021-11
Size	p. 135-147.
Publishing place	Elsevier B.V.
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	1092300-7
ISSN	1878-7320 ; 1001-0742
ISSN (online)	1878-7320
ISSN	1001-0742
DOI	10.1016/j.jes.2021.03.044
Database	NAL-Catalogue (AGRICOLA)

In stock of ZB MED Bonn / Germany

Z 7630: Show issues

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- See ZB MED holdings
- Order with fees

Book ; Online: Cross-modal Memory Networks for Radiology Report Generation

Chen, Zhihong / Shen, Yaling / Song, Yan / Wan, Xiang

2022

Abstract: Medical imaging plays a significant role in clinical practice of medical diagnosis, where the text reports of the images are essential in understanding them and facilitating later treatments. By generating the reports automatically, it is beneficial to ... ...

Abstract	Medical imaging plays a significant role in clinical practice of medical diagnosis, where the text reports of the images are essential in understanding them and facilitating later treatments. By generating the reports automatically, it is beneficial to help lighten the burden of radiologists and significantly promote clinical automation, which already attracts much attention in applying artificial intelligence to medical domain. Previous studies mainly follow the encoder-decoder paradigm and focus on the aspect of text generation, with few studies considering the importance of cross-modal mappings and explicitly exploit such mappings to facilitate radiology report generation. In this paper, we propose a cross-modal memory networks (CMN) to enhance the encoder-decoder framework for radiology report generation, where a shared memory is designed to record the alignment between images and texts so as to facilitate the interaction and generation across modalities. Experimental results illustrate the effectiveness of our proposed model, where state-of-the-art performance is achieved on two widely used benchmark datasets, i.e., IU X-Ray and MIMIC-CXR. Further analyses also prove that our model is able to better align information from radiology images and texts so as to help generating more accurate reports in terms of clinical indicators. Comment: Natural Language Processing. 11 pages, 6 figures. ACL-IJCNLP 2021
Keywords	Computer Science - Computation and Language
Subject code	004
Publishing date	2022-04-27
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Enhanced metagenomic deep learning for disease prediction and consistent signature recognition by restructured microbiome 2D representations.

Shen, Wan Xiang / Liang, Shu Ran / Jiang, Yu Yang / Chen, Yu Zong

Patterns (New York, N.Y.)

2022 Volume 4, Issue 1, Page(s) 100658

Abstract: Metagenomic analysis has been explored for disease diagnosis and biomarker discovery. Low sample sizes, high dimensionality, and sparsity of metagenomic data challenge metagenomic investigations. Here, an unsupervised microbial embedding, grouping, and ... ...

Abstract	Metagenomic analysis has been explored for disease diagnosis and biomarker discovery. Low sample sizes, high dimensionality, and sparsity of metagenomic data challenge metagenomic investigations. Here, an unsupervised microbial embedding, grouping, and mapping algorithm (MEGMA) was developed to transform metagenomic data into individualized multichannel microbiome 2D representation by manifold learning and clustering of microbial profiles (e.g., composition, abundance, hierarchy, and taxonomy). These 2D representations enable enhanced disease prediction by established ConvNet-based AggMapNet models, outperforming the commonly used machine learning and deep learning models in metagenomic benchmark datasets. These 2D representations combined with AggMapNet explainable module robustly identified more reliable and replicable disease-prediction microbes (biomarkers). Employing the MEGMA-AggMapNet pipeline for biomarker identification from 5 disease datasets, 84% of the identified biomarkers have been described in over 74 distinct works as important for these diseases. Moreover, the method also discovered highly consistent sets of biomarkers in cross-cohort colorectal cancer (CRC) patients and microbial shifts in different CRC stages.
Language	English
Publishing date	2022-12-15
Publishing country	United States
Document type	Journal Article
ISSN	2666-3899
ISSN (online)	2666-3899
DOI	10.1016/j.patter.2022.100658
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED