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  1. Article ; Online: CSA: A Channel-Separated Attention Module for Enhancing MRI Reconstruction.

    Song, Mengdie / Hao, Xiaohan / Qi, Fulang

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

    2023  Volume 2023, Page(s) 1–4

    Abstract: Channel attention mechanisms have been proven to effectively enhance network performance in various visual tasks, including the Magnetic Resonance Imaging (MRI) reconstruction task. Channel attention mechanisms typically involve channel dimensionality ... ...

    Abstract Channel attention mechanisms have been proven to effectively enhance network performance in various visual tasks, including the Magnetic Resonance Imaging (MRI) reconstruction task. Channel attention mechanisms typically involve channel dimensionality reduction and cross-channel interaction operations to achieve complexity reduction and generate more effective weights of channels. However, the operations may negatively impact MRI reconstruction performance since it was found that there is no discernible correlation between adjacent channels and the low information value in some feature maps. Therefore, we proposed the Channel-Separated Attention (CSA) module tailored for MRI reconstruction networks. Each layer of the CSA module avoids compressing channels, thereby allowing for lossless information transmission. Additionally, we employed the Hadamard product to realize that each channel's importance weight was generated solely based on itself, avoiding cross-channel interaction and reducing the computational complexity. We replaced the original channel attention module with the CSA module in an advanced MRI reconstruction network and noticed that CSA module achieved superior reconstruction performance with fewer parameters. Furthermore, we conducted comparative experiments with state-of-the-art channel attention modules on an identical network backbone, CSA module achieved competitive reconstruction outcomes with only approximately 1.036% parameters of the Squeeze-and-Excitation (SE) module. Overall, the CSA module makes an optimal trade-off between complexity and reconstruction quality to efficiently and effectively enhance MRI reconstruction. The code is available at https://github.com/smd1997/CSA-Net.
    MeSH term(s) Magnetic Resonance Imaging ; Image Processing, Computer-Assisted
    Language English
    Publishing date 2023-12-27
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2694-0604
    ISSN (online) 2694-0604
    DOI 10.1109/EMBC40787.2023.10340098
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  2. Article ; Online: Fish skin mucosal surface becomes a barrier of antibiotic resistance genes under apramycin exposure.

    Li, Wenpeng / Zhang, Xiaohan / Hao, Xiaohan / Xin, Rui / Zhang, Ying / Ma, Yongzheng / Niu, Zhiguang

    Environmental research

    2024  Volume 252, Issue Pt 3, Page(s) 118930

    Abstract: Antibiotic resistance genes (ARGs) are a kind of emerging environmental contamination, and are commonly found in antibiotic application situations, attracting wide attention. Fish skin mucosal surface (SMS), as the contact interface between fish and ... ...

    Abstract Antibiotic resistance genes (ARGs) are a kind of emerging environmental contamination, and are commonly found in antibiotic application situations, attracting wide attention. Fish skin mucosal surface (SMS), as the contact interface between fish and water, is the first line of defense against external pollutant invasion. Antibiotics are widely used in aquaculture, and SMS may be exposed to antibiotics. However, what happens to SMS when antibiotics are applied, and whether ARGs are enriched in SMS are not clear. In this study, Zebrafish (Danio rerio) were exposed to antibiotic and antibiotic resistant bacteria in the laboratory to simulate the aquaculture situation, and the effects of SMS on the spread of ARGs were explored. The results showed that SMS maintained the stability of the bacterial abundance and diversity under apramycin (APR) and bacterial exposure effectively. Until 11 days after stopping APR exposure, the abundance of ARGs in SMS (mean value was 3.32 × 10
    Language English
    Publishing date 2024-04-13
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 205699-9
    ISSN 1096-0953 ; 0013-9351
    ISSN (online) 1096-0953
    ISSN 0013-9351
    DOI 10.1016/j.envres.2024.118930
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    Zs.A 726: Show issues Location:
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  3. Article: Linear fine-tuning: a linear transformation based transfer strategy for deep MRI reconstruction.

    Bi, Wanqing / Xv, Jianan / Song, Mengdie / Hao, Xiaohan / Gao, Dayong / Qi, Fulang

    Frontiers in neuroscience

    2023  Volume 17, Page(s) 1202143

    Abstract: Introduction: Fine-tuning (FT) is a generally adopted transfer learning method for deep learning-based magnetic resonance imaging (MRI) reconstruction. In this approach, the reconstruction model is initialized with pre-trained weights derived from a ... ...

    Abstract Introduction: Fine-tuning (FT) is a generally adopted transfer learning method for deep learning-based magnetic resonance imaging (MRI) reconstruction. In this approach, the reconstruction model is initialized with pre-trained weights derived from a source domain with ample data and subsequently updated with limited data from the target domain. However, the direct full-weight update strategy can pose the risk of "catastrophic forgetting" and overfitting, hindering its effectiveness. The goal of this study is to develop a zero-weight update transfer strategy to preserve pre-trained generic knowledge and reduce overfitting.
    Methods: Based on the commonality between the source and target domains, we assume a linear transformation relationship of the optimal model weights from the source domain to the target domain. Accordingly, we propose a novel transfer strategy, linear fine-tuning (LFT), which introduces scaling and shifting (SS) factors into the pre-trained model. In contrast to FT, LFT only updates SS factors in the transfer phase, while the pre-trained weights remain fixed.
    Results: To evaluate the proposed LFT, we designed three different transfer scenarios and conducted a comparative analysis of FT, LFT, and other methods at various sampling rates and data volumes. In the transfer scenario between different contrasts, LFT outperforms typical transfer strategies at various sampling rates and considerably reduces artifacts on reconstructed images. In transfer scenarios between different slice directions or anatomical structures, LFT surpasses the FT method, particularly when the target domain contains a decreasing number of training images, with a maximum improvement of up to 2.06 dB (5.89%) in peak signal-to-noise ratio.
    Discussion: The LFT strategy shows great potential to address the issues of "catastrophic forgetting" and overfitting in transfer scenarios for MRI reconstruction, while reducing the reliance on the amount of data in the target domain. Linear fine-tuning is expected to shorten the development cycle of reconstruction models for adapting complicated clinical scenarios, thereby enhancing the clinical applicability of deep MRI reconstruction.
    Language English
    Publishing date 2023-06-20
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2411902-7
    ISSN 1662-453X ; 1662-4548
    ISSN (online) 1662-453X
    ISSN 1662-4548
    DOI 10.3389/fnins.2023.1202143
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  4. Article ; Online: A novel marine bacterium Exiguobacterium marinum a-1 isolated from in situ plastisphere for degradation of additive-free polypropylene.

    Sun, Yueling / Zhang, Ying / Hao, Xiaohan / Zhang, Xiaohan / Ma, Yongzheng / Niu, Zhiguang

    Environmental pollution (Barking, Essex : 1987)

    2023  Volume 336, Page(s) 122390

    Abstract: As the ecological niche most closely associated with polymers, microorganisms in the 'plastisphere' have great potential for plastics degradation. Microorganisms isolated from the 'plastisphere' could colonize and degrade commercial plastics containing ... ...

    Abstract As the ecological niche most closely associated with polymers, microorganisms in the 'plastisphere' have great potential for plastics degradation. Microorganisms isolated from the 'plastisphere' could colonize and degrade commercial plastics containing different additives, but the observed weight loss and surface changes were most likely caused by releasing the additives rather than actual degradation of the plastics itself. Unlike commercial plastics that contain additives, whether marine microorganisms in the 'plastisphere' have adapted to additive-free plastics as a surface to colonize and potentially degrade is not yet known. Herein, a novel marine bacterium, Exiguobacterium marinum a-1, was successfully isolated from mature 'plastisphere' that had been deployed in situ for up to 20 months. Strain a-1 could use additive-free polypropylene (PP) films as its primary energy and carbon source. After strain a-1 was incubated with additive-free PP films for 80 days, the weight of films decreased by 9.2%. The ability of strain a-1 to rapidly form biofilms and effectively colonize the surface of additive-free PP films was confirmed by Scanning Electron Microscopy (SEM), as reflected by the increase in roughness and visible craters on the surface of additive-free PP films. Additionally, the functional groups of -CO, -C-H, and -OH were identified on the treated additive-free PP films according to Fourier Transform Infrared (FTIR). Genomic data from strain a-1 revealed a suite of key genes involved in biosurfactant synthesis, flagellar assembly, and cellular chemotaxis, contributing to its rapid biofilm formation on hydrophobic polymer surfaces. In particular, key enzymes that may be responsible for the degradation of additive-free PP films, such as glutathione peroxidase, cytochrome p450 and esterase were also recognized. This study highlights the potential of microorganisms present in the 'plastisphere' to metabolize plastic polymers and points to the intrinsic importance of the new strain a-1 in the mitigation of plastic pollution.
    MeSH term(s) Polypropylenes ; Plastics ; Polymers ; Bacteria/genetics ; Bacillaceae
    Chemical Substances Polypropylenes ; Plastics ; Polymers
    Language English
    Publishing date 2023-08-17
    Publishing country England
    Document type Journal Article
    ZDB-ID 280652-6
    ISSN 1873-6424 ; 0013-9327 ; 0269-7491
    ISSN (online) 1873-6424
    ISSN 0013-9327 ; 0269-7491
    DOI 10.1016/j.envpol.2023.122390
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    Zs.A 2599: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (2.OG)
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  5. Article ; Online: Enzyme/pH Dual-Responsive Engineered Nanoparticles for Improved Tumor Immuno-Chemotherapy.

    Liu, Zefeng / Hao, Xiaohan / Qian, Jieying / Zhang, Hao / Bao, Hui / Yang, Qiong / Gu, Weiguang / Huang, Xiaowan / Zhang, Yunjiao

    ACS applied materials & interfaces

    2024  Volume 16, Issue 10, Page(s) 12951–12964

    Abstract: Combining immune checkpoint blockade (ICB) therapy with chemotherapy can enhance the efficacy of ICB and expand its indications. However, the limited tumor specificity of chemotherapy drugs results in severe adverse reactions. Additionally, the low ... ...

    Abstract Combining immune checkpoint blockade (ICB) therapy with chemotherapy can enhance the efficacy of ICB and expand its indications. However, the limited tumor specificity of chemotherapy drugs results in severe adverse reactions. Additionally, the low tissue penetration and immune-related adverse events associated with monoclonal antibodies restrict their widespread application. To address challenges faced by traditional combination therapies, we design a dual-responsive engineered nanoparticle based on ferritin (denoted as CMFn@OXA), achieving tumor-targeted delivery and controlled release of the anti-PD-L1 peptide CLP002 and oxaliplatin (OXA). Our results demonstrate that CMFn@OXA not only exhibits tumor-specific accumulation but also responds to matrix metalloproteinase-2/9 (MMP-2/9), facilitating the controlled release of CLP002 to block PD-1/PD-L1 interaction. Simultaneously, it ensures the precise delivery of the OXA to tumor cells and its subsequent release within the acidic environment of lysosomes, thereby fostering a synergistic therapeutic effect. Compared to traditional combination therapies, CMFn@OXA demonstrates superior performance in inhibiting tumor growth, extending the survival of tumor-bearing mice, and exhibiting excellent biocompatibility. Collectively, our results highlight CMFn@OXA as a novel and promising strategy in the field of cancer immunotherapy.
    MeSH term(s) Animals ; Mice ; Matrix Metalloproteinase 2 ; Delayed-Action Preparations ; Neoplasms/drug therapy ; Oxaliplatin/pharmacology ; Immunotherapy/methods ; Nanoparticles ; Hydrogen-Ion Concentration ; Tumor Microenvironment ; Cell Line, Tumor
    Chemical Substances Matrix Metalloproteinase 2 (EC 3.4.24.24) ; Delayed-Action Preparations ; Oxaliplatin (04ZR38536J)
    Language English
    Publishing date 2024-02-29
    Publishing country United States
    Document type Journal Article
    ISSN 1944-8252
    ISSN (online) 1944-8252
    DOI 10.1021/acsami.3c18348
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  6. Article ; Online: Biofilms retard the desorption of benzo(a)pyrene from polyethylene pellets in the marine environment.

    Hao, Xiaohan / Zhang, Ying / Sun, Yueling / Liu, Hongtao / Zhang, Xiaohan / Li, Xiaofeng / Ma, Yongzheng / Niu, Zhiguang

    Marine pollution bulletin

    2023  Volume 195, Page(s) 115453

    Abstract: Microplastics are emerging as vectors for the transport hydrophobic organic compounds (HOCs) in aquatic environments, however, their impact is poorly understood due to the lack of field studies. In this study, the pristine and benzo(a)pyrene (B[a]P) ... ...

    Abstract Microplastics are emerging as vectors for the transport hydrophobic organic compounds (HOCs) in aquatic environments, however, their impact is poorly understood due to the lack of field studies. In this study, the pristine and benzo(a)pyrene (B[a]P) adsorbed polyethylene (PE) pellets were placed at Haihe Estuary (Tianjin, China) for 80 days to investigate desorption behavior. Combining laboratory and in situ experiments, this study firstly verified that the intra-particle diffusion was the rate-limiting step for the desorption process of B[a]P from PE microplastics under different environmental conditions. By hindering the desorption and modifying MPs surface, biofilm might play a key role in desorption process, leading to the apparent hysteresis of the field desorption process at our time scale. Potential degradation of the polymer and B[a]P by biofilms, however, would support continuing desorption. The study explored the interaction of biofilm and MPs-contaminants mixture and its implications for the environmental fate of HOCs.
    MeSH term(s) Plastics/chemistry ; Polyethylene ; Microplastics ; Benzo(a)pyrene ; Water Pollutants, Chemical/analysis ; Organic Chemicals ; Biofilms ; Adsorption
    Chemical Substances Plastics ; Polyethylene (9002-88-4) ; Microplastics ; Benzo(a)pyrene (3417WMA06D) ; Water Pollutants, Chemical ; Organic Chemicals
    Language English
    Publishing date 2023-09-01
    Publishing country England
    Document type Journal Article
    ZDB-ID 2001296-2
    ISSN 1879-3363 ; 0025-326X
    ISSN (online) 1879-3363
    ISSN 0025-326X
    DOI 10.1016/j.marpolbul.2023.115453
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  7. Article ; Online: A hybrid convolutional neural network for super-resolution reconstruction of MR images.

    Zheng, Yingjie / Zhen, Bowen / Chen, Aichi / Qi, Fulang / Hao, Xiaohan / Qiu, Bensheng

    Medical physics

    2020  Volume 47, Issue 7, Page(s) 3013–3022

    Abstract: Purpose: Spatial resolution is an important parameter for magnetic resonance imaging (MRI). High-resolution MR images provide detailed information and benefit subsequent image analysis. However, higher resolution MR images come at the expense of longer ... ...

    Abstract Purpose: Spatial resolution is an important parameter for magnetic resonance imaging (MRI). High-resolution MR images provide detailed information and benefit subsequent image analysis. However, higher resolution MR images come at the expense of longer scanning time and lower signal-to-noise ratios (SNRs). Using algorithms to improve image resolution can mitigate these limitations. Recently, some convolutional neural network (CNN)-based super-resolution (SR) algorithms have flourished on MR image reconstruction. However, most algorithms usually adopt deeper network structures to improve the performance.
    Methods: In this study, we propose a novel hybrid network (named HybridNet) to improve the quality of SR images by increasing the width of the network. Specifically, the proposed hybrid block combines a multipath structure and variant dense blocks to extract abundant features from low-resolution images. Furthermore, we fully exploit the hierarchical features from different hybrid blocks to reconstruct high-quality images.
    Results: All SR algorithms are evaluated using three MR image datasets and the proposed HybridNet outperformed the comparative methods with peak a signal-to-noise ratio (PSNR) of 42.12 ± 0.92 dB, 38.60 ± 2.46 dB, 35.17 ± 2.96 dB and a structural similarity index (SSIM) of 0.9949 ± 0.0015, 0.9892 ± 0.0034, 0.9740 ± 0.0064, respectively. Besides, our proposed network can reconstruct high-quality images on an unseen MR dataset with PSNR of 33.27 ± 1.56 and SSIM of 0.9581 ± 0.0068.
    Conclusions: The results demonstrate that HybridNet can reconstruct high-quality SR images from degraded MR images and has good generalization ability. It also can be leveraged to assist the task of image analysis or processing.
    MeSH term(s) Algorithms ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging ; Neural Networks, Computer ; Signal-To-Noise Ratio
    Language English
    Publishing date 2020-04-27
    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.14152
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    Zs.A 1210: 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)

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  8. Article ; Online: A Radiomics-based Approach for Predicting Early Recurrence in Intrahepatic Cholangiocarcinoma after Surgical Resection: A Multicenter Study.

    Hao, Xiaohan / Liu, Bing / Hu, Xiaofei / Wei, Jingwei / Han, Yuqi / Liu, Xianchuang / Chen, Zhiyu / Li, Jiaping / Bai, Jie / Chen, Yongliang / Wang, Jian / Niu, Meng / Tian, Jie

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

    2021  Volume 2021, Page(s) 3659–3662

    Abstract: This work aimed to develop a noninvasive and reliable computed tomography (CT)-based imaging biomarker to predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICC) via radiomics analysis. In this retrospective study, a total of 177 ICC ... ...

    Abstract This work aimed to develop a noninvasive and reliable computed tomography (CT)-based imaging biomarker to predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICC) via radiomics analysis. In this retrospective study, a total of 177 ICC patients were enrolled from three independent hospitals. Radiomic features were extracted on CT images, then 11 feature selection algorithms and 4 classifiers were to conduct a multi-strategy radiomics modeling. Six established radiomics models were selected as stable ones by robustness-based rule. Among those models, Max-Relevance Min-Redundancy (MRMR) combined with Gradient Boosting Machine (GBM) yielded the highest areas under the receiver operating characteristics curve (AUCs) of 0.802 (95% confidence interval [CI]: 0.727-0.876) and 0.781 (95% CI: 0.655-0.907) in the training and test cohorts, respectively. To evaluate the generalization of the developed radiomics model, stratification analysis was performed regarding different centers. The MRMR-GBM-based model manifested good generalization with comparable AUCs in each hospital (p > 0.05 for paired comparison). Thus, the MRMR-GBM-based model could offer a potential imaging biomarker to assist the prediction of ER in ICC in a noninvasive manner.Clinical Relevance-The proposed radiomics model achieved satisfactory accuracy and good generalization ability in predicting ER in ICC, which might assist personalized surveillance and clinical treatment strategy making.
    MeSH term(s) Bile Duct Neoplasms/diagnostic imaging ; Bile Duct Neoplasms/surgery ; Bile Ducts, Intrahepatic/diagnostic imaging ; Bile Ducts, Intrahepatic/surgery ; Cholangiocarcinoma/diagnostic imaging ; Cholangiocarcinoma/surgery ; Humans ; Retrospective Studies ; Tomography, X-Ray Computed
    Language English
    Publishing date 2021-12-07
    Publishing country United States
    Document type Journal Article ; Multicenter Study ; Research Support, Non-U.S. Gov't
    ISSN 2694-0604
    ISSN (online) 2694-0604
    DOI 10.1109/EMBC46164.2021.9630029
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: A deep learning risk prediction model for overall survival in patients with gastric cancer: A multicenter study.

    Zhang, Liwen / Dong, Di / Zhang, Wenjuan / Hao, Xiaohan / Fang, Mengjie / Wang, Shuo / Li, Wuchao / Liu, Zaiyi / Wang, Rongpin / Zhou, Junlin / Tian, Jie

    Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology

    2020  Volume 150, Page(s) 73–80

    Abstract: Background and purpose: Risk prediction of overall survival (OS) is crucial for gastric cancer (GC) patients to assess the treatment programs and may guide personalized medicine. A novel deep learning (DL) model was proposed to predict the risk for OS ... ...

    Abstract Background and purpose: Risk prediction of overall survival (OS) is crucial for gastric cancer (GC) patients to assess the treatment programs and may guide personalized medicine. A novel deep learning (DL) model was proposed to predict the risk for OS based on computed tomography (CT) images.
    Materials and methods: We retrospectively collected 640 patients from three independent centers, which were divided into a training cohort (center 1 and center 2, n = 518) and an external validation cohort (center 3, n = 122). We developed a DL model based on the architecture of residual convolutional neural network. We augmented the size of training dataset by image transformations to avoid overfitting. We also developed radiomics and clinical models for comparison. The performance of the three models were comprehensively assessed.
    Results: Totally 518 patients were prepared by data augmentation and fed into DL model. The trained DL model significantly classified patients into high-risk and low-risk groups in training cohort (P-value <0.001, concordance index (C-index): 0.82, hazard ratio (HR): 9.79) and external validation cohort (P-value <0.001, C-index: 0.78, HR: 11.76). Radiomics model was developed with selected 24 features and clinical model was developed with three significant clinical variables (P-value <0.05). The comparison illustrated DL model had the best performance for risk prediction of OS according to the C-index (training: DL vs Clinical vs Radiomics = 0.82 vs 0.73 vs 0.66; external validation: 0.78 vs 0.71 vs 0.72).
    Conclusion: The DL model is a powerful model for risk assessment, and potentially serves as an individualized recommender for decision-making in GC patients.
    MeSH term(s) Deep Learning ; Humans ; Prognosis ; Retrospective Studies ; Stomach Neoplasms/diagnostic imaging ; Tomography, X-Ray Computed
    Language English
    Publishing date 2020-06-12
    Publishing country Ireland
    Document type Journal Article ; Multicenter Study ; Research Support, Non-U.S. Gov't
    ZDB-ID 605646-5
    ISSN 1879-0887 ; 0167-8140
    ISSN (online) 1879-0887
    ISSN 0167-8140
    DOI 10.1016/j.radonc.2020.06.010
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    Zs.A 1926: Show issues Location:
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  10. Article ; Online: FAAH served a key membrane-anchoring and stabilizing role for NLRP3 protein independently of the endocannabinoid system.

    Zhu, Yangyang / Zhang, Hao / Mao, Huawei / Zhong, Suqin / Huang, Yubing / Chen, Sirong / Yan, Kai / Zhao, Zhibin / Hao, Xiaohan / Zhang, Yue / Yao, Han / Huang, Xiaowan / Wang, Meimei / Zhang, Wenbin / Li, Juan / Meng, Guangxun / Qin, Xiaohua / Ye, Zhiming / Shen, Jiani /
    Song, Yang / Xu, Youcui / Yang, Zhenyu / Wang, Liansheng / Zhang, Yunjiao / Wen, Longping

    Cell death and differentiation

    2022  Volume 30, Issue 1, Page(s) 168–183

    Abstract: NLRP3, the sensor protein of the NLRP3 inflammasome, plays central roles in innate immunity. Over-activation of NLRP3 inflammasome contributes to the pathogenesis of a variety of inflammatory diseases, while gain-of-function mutations of NLRP3 cause ... ...

    Abstract NLRP3, the sensor protein of the NLRP3 inflammasome, plays central roles in innate immunity. Over-activation of NLRP3 inflammasome contributes to the pathogenesis of a variety of inflammatory diseases, while gain-of-function mutations of NLRP3 cause cryopyrin-associated periodic syndromes (CAPS). NLRP3 inhibitors, particularly those that inhibit inflammasome assembly and activation, are being intensively pursued, but alternative approaches for targeting NLRP3 would be highly desirable. During priming NLRP3 protein is synthesized on demand and becomes attached to the membranes of ER and mitochondria. Here, we show that fatty acid amide hydrolase (FAAH), the key integral membrane enzyme in the endocannabinoid system, unexpectedly served the critical membrane-anchoring and stabilizing role for NLRP3. The specific interaction between NLRP3 and FAAH, mediated by the NACHT and LRR domains of NLRP3 and the amidase signature sequence of FAAH, was essential for preventing CHIP- and NBR1-mediated selective autophagy of NLRP3. Heterozygous knockout of FAAH, resulting in ~50% reduction in both FAAH and NLRP3 expression, was sufficient to substantially inhibit the auto-inflammatory phenotypes of the NLRP3-R258W knock-in mice, while homozygous FAAH loss almost completely abrogates these phenotypes. Interestingly, select FAAH inhibitors, in particular URB597 and PF-04457845, disrupted NLRP3-FAAH interaction and induced autophagic NLRP3 degradation, leading to diminished inflammasome activation in mouse macrophage cells as well as in peripheral blood mononuclear cells isolated from CAPS patients. Our results unraveled a novel NLRP3-stabilizing mechanism and pinpointed NLRP3-FAAH interaction as a potential drug target for CAPS and other NLRP3-driven diseases.
    MeSH term(s) Mice ; Animals ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism ; Inflammasomes/metabolism ; Endocannabinoids/metabolism ; Leukocytes, Mononuclear/metabolism ; Cryopyrin-Associated Periodic Syndromes/genetics ; Cryopyrin-Associated Periodic Syndromes/metabolism ; Amidohydrolases/genetics
    Chemical Substances NLR Family, Pyrin Domain-Containing 3 Protein ; Inflammasomes ; Endocannabinoids ; fatty-acid amide hydrolase (EC 3.5.1.-) ; Amidohydrolases (EC 3.5.-) ; Nlrp3 protein, mouse
    Language English
    Publishing date 2022-09-14
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1225672-9
    ISSN 1476-5403 ; 1350-9047
    ISSN (online) 1476-5403
    ISSN 1350-9047
    DOI 10.1038/s41418-022-01054-4
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