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Article ; Online: Psychological crisis interventions in Sichuan Province during the 2019 novel coronavirus outbreak.

Zhou, Xiaobo

2020 Volume 286, Page(s) 112895

Keywords	covid19
Language	English
Publishing date	2020-02-26
Publishing country	Ireland
Document type	Letter
ZDB-ID	445361-x
ISSN	1872-7123 ; 1872-7506 ; 0925-4927 ; 0165-1781
ISSN (online)	1872-7123 ; 1872-7506
ISSN	0925-4927 ; 0165-1781
DOI	10.1016/j.psychres.2020.112895
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Zs.A 1541: Show issues

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Article ; Online: Study of prognostic splicing factors in cancer using machine learning approaches.

Yang, Mengyuan / Liu, Jiajia / Kim, Pora / Zhou, Xiaobo

Human molecular genetics

2024

Abstract: Splicing factors (SFs) are the major RNA-binding proteins (RBPs) and key molecules that regulate the splicing of mRNA molecules through binding to mRNAs. The expression of splicing factors is frequently deregulated in different cancer types, causing the ... ...

Abstract	Splicing factors (SFs) are the major RNA-binding proteins (RBPs) and key molecules that regulate the splicing of mRNA molecules through binding to mRNAs. The expression of splicing factors is frequently deregulated in different cancer types, causing the generation of oncogenic proteins involved in cancer hallmarks. In this study, we investigated the genes that encode RNA-binding proteins and identified potential splicing factors that contribute to the aberrant splicing applying a random forest classification model. The result suggested 56 splicing factors were related to the prognosis of 13 cancers, two SF complexes in liver hepatocellular carcinoma, and one SF complex in esophageal carcinoma. Further systematic bioinformatics studies on these cancer prognostic splicing factors and their related alternative splicing events revealed the potential regulations in a cancer-specific manner. Our analysis found high ILF2-ILF3 expression correlates with poor prognosis in LIHC through alternative splicing. These findings emphasize the importance of SFs as potential indicators for prognosis or targets for therapeutic interventions. Their roles in cancer exhibit complexity and are contingent upon the specific context in which they operate. This recognition further underscores the need for a comprehensive understanding and exploration of the role of SFs in different types of cancer, paving the way for their potential utilization in prognostic assessments and the development of targeted therapies.
Language	English
Publishing date	2024-03-27
Publishing country	England
Document type	Journal Article
ZDB-ID	1108742-0
ISSN	1460-2083 ; 0964-6906
ISSN (online)	1460-2083
ISSN	0964-6906
DOI	10.1093/hmg/ddae047
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Zs.A 3469: Show issues

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Article ; Online: Advances in Non-Type 2 Asthma in the Severe Cases: from molecular insights to novel treatment strategies.

Liu, Tao / Prescott, Woodruff G / Zhou, Xiaobo

The European respiratory journal

2024

Abstract: Asthma is a prevalent pulmonary disease that affects nearly 300 million people worldwide and imposes a substantial economic burden. While medication can effectively control symptoms in some patients, severe asthma attacks, driven by airway-inflammation ... ...

Abstract	Asthma is a prevalent pulmonary disease that affects nearly 300 million people worldwide and imposes a substantial economic burden. While medication can effectively control symptoms in some patients, severe asthma attacks, driven by airway-inflammation induced by environmental and infectious exposures, continue to be a major cause of asthma-related mortality. Heterogenous phenotypes of asthma include type 2 (T2) and non-T2 asthma. Non-T2 asthma is often observed in patients with severe and/or steroid-resistant asthma. This review will cover the molecular mechanisms, clinical phenotypes, causes and promising treatment of non-T2 severe asthma. Specifically, we will discuss the signaling pathways for non-T2 asthma including the activation of inflammasomes, interferon responses, and IL-17 pathways, and their contributions to the subtypes, progression, and severity of non-T2 asthma. Understanding the molecular mechanisms and genetic determinants underlying non-T2 asthma could form the basis for precision medicine in severe asthma treatment.
Language	English
Publishing date	2024-05-02
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	639359-7
ISSN	1399-3003 ; 0903-1936
ISSN (online)	1399-3003
ISSN	0903-1936
DOI	10.1183/13993003.00826-2023
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Zs.A 2322: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 292: Show issues

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Article: A Cell Cycle-aware Network for Data Integration and Label Transferring of Single-cell RNA-seq and ATAC-seq.

Liu, Jiajia / Ma, Jian / Wen, Jianguo / Zhou, Xiaobo

bioRxiv : the preprint server for biology

2024

Abstract: In recent years, the integration of single-cell multi-omics data has provided a more comprehensive understanding of cell functions and internal regulatory mechanisms from a non-single omics perspective, but it still suffers many challenges, such as omics- ...

Abstract	In recent years, the integration of single-cell multi-omics data has provided a more comprehensive understanding of cell functions and internal regulatory mechanisms from a non-single omics perspective, but it still suffers many challenges, such as omics-variance, sparsity, cell heterogeneity and confounding factors. As we know, cell cycle is regarded as a confounder when analyzing other factors in single-cell RNA-seq data, but it's not clear how it will work on the integrated single-cell multi-omics data. Here, we developed a Cell Cycle-Aware Network (CCAN) to remove cell cycle effects from the integrated single-cell multi-omics data while keeping the cell type-specific variations. This is the first computational model to study the cell-cycle effects in the integration of single-cell multi-omics data. Validations on several benchmark datasets show the out-standing performance of CCAN in a variety of downstream analyses and applications, including removing cell cycle effects and batch effects of scRNA-seq datasets from different protocols, integrating paired and unpaired scRNA-seq and scATAC-seq data, accurately transferring cell type labels from scRNA-seq to scATAC-seq data, and characterizing the differentiation process from hematopoietic stem cells to different lineages in the integration of differentiation data.
Language	English
Publishing date	2024-02-02
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.01.31.578213
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Article: Single-cell Landscape of Malignant Transition: Unraveling Cancer Cell-of-Origin and Heterogeneous Tissue Microenvironment.

Luo, Ruihan / Liu, Jiajia / Wen, Jianguo / Zhou, Xiaobo

Research square

2024

Abstract: Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by ... ...

Abstract	Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by leveraging data from 1396 samples spanning 13 major tissues. Within transitional stem-like subpopulations highly enriched in precancers and cancers, we identified 30 recurring cellular states strongly linked to malignancy, including hypoxia and epithelial senescence, revealing a high degree of plasticity in epithelial stem cells. By characterizing dynamics in stem-cell crosstalk with the microenvironment along the pseudotime axis, we found differential roles of ANXA1 at different stages of tumor development. In precancerous stages, reduced ANXA1 levels promoted monocyte differentiation toward M1 macrophages and inflammatory responses, whereas during malignant progression, upregulated ANXA1 fostered M2 macrophage polarization and cancer-associated fibroblast transformation by increasing TGF-β production. Our spatiotemporal analysis further provided insights into mechanisms responsible for immunosuppression and a potential target to control evolution of precancer and mitigate the risk for cancer development.
Language	English
Publishing date	2024-04-05
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-4085185/v1
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Article ; Online: CCSynergy: an integrative deep-learning framework enabling context-aware prediction of anti-cancer drug synergy.

Hosseini, Sayed-Rzgar / Zhou, Xiaobo

Briefings in bioinformatics

2022 Volume 24, Issue 1

Abstract: Combination therapy is a promising strategy for confronting the complexity of cancer. However, experimental exploration of the vast space of potential drug combinations is costly and unfeasible. Therefore, computational methods for predicting drug ... ...

Abstract	Combination therapy is a promising strategy for confronting the complexity of cancer. However, experimental exploration of the vast space of potential drug combinations is costly and unfeasible. Therefore, computational methods for predicting drug synergy are much needed for narrowing down this space, especially when examining new cellular contexts. Here, we thus introduce CCSynergy, a flexible, context aware and integrative deep-learning framework that we have established to unleash the potential of the Chemical Checker extended drug bioactivity profiles for the purpose of drug synergy prediction. We have shown that CCSynergy enables predictions of superior accuracy, remarkable robustness and improved context generalizability as compared to the state-of-the-art methods in the field. Having established the potential of CCSynergy for generating experimentally validated predictions, we next exhaustively explored the untested drug combination space. This resulted in a compendium of potentially synergistic drug combinations on hundreds of cancer cell lines, which can guide future experimental screens.
MeSH term(s)	Drug Synergism ; Deep Learning ; Computational Biology/methods ; Cell Line, Tumor ; Antineoplastic Agents/pharmacology ; Antineoplastic Agents/therapeutic use ; Drug Combinations
Chemical Substances	Antineoplastic Agents ; Drug Combinations
Language	English
Publishing date	2022-12-23
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbac588
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Zs.A 6262: Show issues

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Article: Psychological crisis interventions in Sichuan Province during the 2019 novel coronavirus outbreak

Zhou, Xiaobo

Psychiatry Res

Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #3033
Database	COVID19

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Article ; Online: A review of numerical simulation in transcatheter aortic valve replacement decision optimization.

Huang, Xuan / Zhang, Guangming / Zhou, Xiaobo / Yang, Xiaoyan

Clinical biomechanics (Bristol, Avon)

2023 Volume 106, Page(s) 106003

Abstract: Background: Recent trials indicated a further expansion of clinical indication of transcatheter aortic valve replacement to younger and low-risk patients. Factors related to longer-term complications are becoming more important for use in these patients. ...

Abstract	Background: Recent trials indicated a further expansion of clinical indication of transcatheter aortic valve replacement to younger and low-risk patients. Factors related to longer-term complications are becoming more important for use in these patients. Accumulating evidence indicates that numerical simulation plays a significant role in improving the outcome of transcatheter aortic valve replacement. Understanding mechanical features' magnitude, pattern, and duration is a topic of ongoing relevance. Methods: We searched the PubMed database using keywords such as "transcatheter aortic valve replacement" and "numerical simulation" and reviewed and summarized relevant literature. Findings: This review integrated recently published evidence into three subtopics: 1) prediction of transcatheter aortic valve replacement outcomes through numerical simulation, 2) implications for surgeons, and 3) trends in transcatheter aortic valve replacement numerical simulation. Interpretations: Our study offers a comprehensive overview of the utilization of numerical simulation in the context of transcatheter aortic valve replacement, and highlights the advantages, potential challenges from a clinical standpoint. The convergence of medicine and engineering plays a pivotal role in enhancing the outcomes of transcatheter aortic valve replacement. Numerical simulation has provided evidence of potential utility for tailored treatments.
MeSH term(s)	Humans ; Aortic Valve/surgery ; Risk Factors ; Transcatheter Aortic Valve Replacement/adverse effects ; Aortic Valve Stenosis/surgery ; Computer Simulation ; Treatment Outcome
Language	English
Publishing date	2023-05-19
Publishing country	England
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't
ZDB-ID	632747-3
ISSN	1879-1271 ; 0268-0033
ISSN (online)	1879-1271
ISSN	0268-0033
DOI	10.1016/j.clinbiomech.2023.106003
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Zs.B 2876: Show issues

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Article ; Online: Centralized contrastive loss with weakly supervised progressive feature extraction for fine-grained common thorax disease retrieval in chest x-ray.

Chen, Fang / You, Lei / Zhao, Weiling / Zhou, Xiaobo

Medical physics

2023 Volume 50, Issue 6, Page(s) 3560–3572

Abstract: Background: Medical images have already become an essential tool for the diagnosis of many diseases. Thus a large number of medical images are being generated due to the daily routine inspection. An efficient image-based disease retrieval system will ... ...

Abstract	Background: Medical images have already become an essential tool for the diagnosis of many diseases. Thus a large number of medical images are being generated due to the daily routine inspection. An efficient image-based disease retrieval system will not only make full use of existing data, but also help physicians to prognosis the diseases. Medical image retrieval is represented by the classification and localization of common thorax diseases in x-ray images. Although extensive efforts have been put into this field, there are still many challenges. Purpose: Most of the existing fine-grained image research methods just apply existing deep learning frameworks in extracting the image features. However, these high-level features mainly focus on the global representations of the object, rather than simultaneously considering the local ones. It requires fine-grained details to classify the images with similar lesion areas. Thus, it is necessary to combine the global features and local ones to make the features more discriminative. On the other hand, training CNN models based on current existing strategies have a high time complexity, and is hard to get the discriminative features mentioned above. In addition, the visual retrieval method of fine-grained medical images still has the problem of insufficient sample data with accurate annotation information. Methods: To address above challenges, we introduced a novel fine-grained medical images retrieval method. First, a centralized contrastive loss (CCLoss) is proposed as our metric learning loss function. Parameters are updated by using the center point, which not only improves the distinguishing performance of features, but also effectively reduces the time complexity of the algorithm. In addition, a weakly supervised progressive feature extraction method is proposed to gradually extract the combined features. And the attention mechanism module is applied to screen the target information after the initial positioning for fine refinement, so as to separate the features with a high degree of discrimination. The retrieval of 14 different chest diseases is evaluated on the chest x-ray datasets. Results: Compared with the existing research methods, the proposed method shows a better retrieval result for Recall@8 by 2.26 Conclusions: The proposed model is capable of learning discriminative representations from chest x-ray datasets, and it achieves better performance compared with other state-of-the-art methods. Therefore, the developed model would be useful in the diagnosis of common thorax disease or unknown chest disease.
MeSH term(s)	Neural Networks, Computer ; X-Rays ; Algorithms ; Thorax/diagnostic imaging ; Radiography
Language	English
Publishing date	2023-01-11
Publishing country	United States
Document type	Journal Article
ZDB-ID	188780-4
ISSN	2473-4209 ; 0094-2405
ISSN (online)	2473-4209
ISSN	0094-2405
DOI	10.1002/mp.16144
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Zs.A 1210: Show issues

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Article: Arthroscopic repair with transosseous sling-suture technique for acute and chronic bony Bankart lesions.

Ji, Xiaoxi / Ye, Lingchao / Hua, Yinghui / Zhou, Xiaobo

Asia-Pacific journal of sports medicine, arthroscopy, rehabilitation and technology

2023 Volume 34, Page(s) 9–14

Abstract: Background: Failure to fix the fractured fragment can result in bony fragment resorption and consequent glenoid bone loss. Current arthroscopic repair techniques might lead to insecure fixation and refracture. The purpose of this study was to evaluate ... ...

Abstract	Background: Failure to fix the fractured fragment can result in bony fragment resorption and consequent glenoid bone loss. Current arthroscopic repair techniques might lead to insecure fixation and refracture. The purpose of this study was to evaluate the effectiveness of the transosseous sling-suture technique for bony Bankart lesions, and to compare the clinical outcomes for acute and chronic bony Bankart lesions treated with this technique. Methods: A retrospective case series consisting of 46 patients with bony fracture of the glenoid rim following traumatic injury was identified from May 2015 to August 2020. The patients were divided into the acute lesion group and the chronic lesion group according to the time from first injury to surgery. The size of bone fragment was used to group the patients into the small and the medium sized fragment groups. All the patients underwent arthroscopic repairs using the transosseous sling-suture technique. Preoperative and postoperative evaluations including Rowe score, West Ontario Shoulder Instability Index (WOSI), Visual Analogue Scale (VAS) for pain scores, ROMs and number of dislocations were recorded. No significant differences were found in the comparisons of postoperative ROMs ang functional outcomes regarding between the small and the medium sized fragment groups. Results: No dislocations occurred for both groups postoperatively. At the last follow-up, all the ROMs (including anterior flexion, abduction, external rotation and internal rotation at the side), the Rowe score, the WOSI score and the VAS score for pain in the both groups were significantly improved compared to the preoperative evaluations (all Conclusion: This arthroscopic transosseous sling-suture repair technique for shoulder anterior instability with acute and chronic bony Bankart lesion can restore joint stability, improve clinical outcomes and range of motion postoperatively. The acute bony Bankart lesion using the current technique can produce better range of motion compared to the chronic lesion. Study design: Retrospective case series; Level of evidence, 4.
Language	English
Publishing date	2023-09-15
Publishing country	Singapore
Document type	Journal Article
ZDB-ID	2817806-3
ISSN	2214-6873
ISSN	2214-6873
DOI	10.1016/j.asmart.2023.08.008
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