Enantioselective Transformations by "1 + x" Synergistic Catalysis with Chiral Primary Amines.

ConspectusSynergistic catalysis is a powerful tool that involves two or more distinctive catalytic systems to activate reaction partners simultaneously, thereby expanding the reactivity space of individual catalysis. As an established catalytic strategy, organocatalysis has found numerous applications in enantioselective transformations under rather mild conditions. Recently, the introduction of other catalytic systems has significantly expanded the reaction space of typical organocatalysis. In this regard, aminocatalysis is a prototypical example of synergistic catalysis. The combination of aminocatalyst and transition metal could be traced back to the early days of organocatalysis and has now been well explored as an enabling catalytic strategy. Particularly, the acid-base properties of aminocatalysis can be significantly expanded to include usually electrophiles generated in situ via metal-catalyzed cycles. Later on, aminocatalyst has also been exploited in synergistically combining with photochemical and electrochemical processes to facilitate redox transformations. However, synergistically combining one type of aminocatalyst with many different catalytic systems remains a great challenge. One of the most daunting challenges is the compatibility of aminocatalysts in coexistence with other catalytic species. As nucleophilic species, aminocatalysts may also bind with metal, which leads to mutual inhibition or even quenching of the individual catalytic activity. In addition, oxidative stability of aminocatalyst is also a non-neglectable issue, which causes difficulties in exploring oxidative enamine transformations.In 2007, we developed a vicinal diamine type of chiral primary aminocatalysts. This class of primary aminocatalysts was developed and evolved as functional and mechanistic mimics to the natural aldolase and has been widely applied in a number of enamine/iminium ion-based transformations. By following a "1 + x" synergistic strategy, the chiral primary amine catalysts were found to work synergistically or cooperatively with a number of transition metal catalysts, such as Pd, Rh, Ag, Co, and Cu, or other organocatalysts, such as B(C6F5)3, ketone, selenium, and iodide. Photocatalysis and electrochemical processes can also be incorporated to work together with the chiral primary amine catalysts. The 1 + x catalytic strategy enabled us to execute unexploited transformations by fine-tuning the acid-base and redox properties of the enamine intermediates and to achieve effective reaction and stereocontrol beyond the reach individually. During these efforts, an unprecedented excited-state chemistry of enamine was uncovered to make possible an effective deracemization process. In this Account, we describe our recent efforts since 2015 in exploring synergistic chiral primary amine catalysis, and the content is categorized according to the type of synergistic partner such that in each section the developed synergistic catalysis, reaction scopes, and mechanistic features are presented and discussed.

Multiple circulating forms of neprilysin detected with novel epitope-directed monoclonal antibodies.

Neprilysin (NEP) is an emerging biomarker for various diseases including heart failure (HF). However, major inter-assay inconsistency in the reported concentrations of circulating NEP and uncertainty with respect to its correlations with type and severity of disease are in part attributed to poorly characterized antibodies supplied in commercial ELISA kits. Validated antibodies with well-defined binding footprints are critical for understanding the biological and clinical context of NEP immunoassay data. To achieve this, we applied in silico epitope prediction and rational peptide selection to generate monoclonal antibodies (mAbs) against spatially distant sites on NEP. One of the selected epitopes contained published N-linked glycosylation sites at N285 and N294. The best antibody pair, mAb 17E11 and 31E1 (glycosylation-sensitive), were characterized by surface plasmon resonance, isotyping, epitope mapping, and western blotting. A validated two-site sandwich NEP ELISA with a limit of detection of 2.15 pg/ml and working range of 13.1-8000 pg/ml was developed with these mAbs. Western analysis using a validated commercial polyclonal antibody (PE pAb) and our mAbs revealed that non-HF and HF plasma NEP circulates as a heterogenous mix of moieties that possibly reflect proteolytic processing, post-translational modifications and homo-dimerization. Both our mAbs detected a ~ 33 kDa NEP fragment which was not apparent with PE pAb, as well as a common ~ 57-60 kDa moiety. These antibodies exhibit different affinities for the various NEP targets. Immunoassay results are dependent on NEP epitopes variably detected by the antibody pairs used, explaining the current discordant NEP measurements derived from different ELISA kits.

Adaptive response of Pseudomonas aeruginosa under serial ciprofloxacin exposure.

Understanding the evolution of antibiotic resistance is important for combating drug-resistant bacteria. In this work, we investigated the adaptive response of Pseudomonas aeruginosa to ciprofloxacin. Ciprofloxacin-susceptible P. aeruginosa ATCC 9027, CIP-E1 (P. aeruginosa ATCC 9027 exposed to ciprofloxacin for 14 days) and CIP-E2 (CIP-E1 cultured in antibiotic-free broth for 10 days) were compared. Phenotypic responses including cell morphology, antibiotic susceptibility, and production of pyoverdine, pyocyanin and rhamnolipid were assessed. Proteomic responses were evaluated using comparative iTRAQ labelling LC-MS/MS to identify differentially expressed proteins (DEPs). Expression of associated genes coding for notable DEPs and their related regulatory genes were checked using quantitative reverse transcriptase PCR. CIP-E1 displayed a heterogeneous morphology, featuring both filamentous cells and cells with reduced length and width. By contrast, although filaments were not present, CIP-E2 still exhibited size reduction. Considering the MIC values, ciprofloxacin-exposed strains developed resistance to fluoroquinolone antibiotics but maintained susceptibility to other antibiotic classes, except for carbapenems. Pyoverdine and pyocyanin production showed insignificant decreases, whereas there was a significant decrease in rhamnolipid production. A total of 1039 proteins were identified, of which approximately 25 % were DEPs. In general, there were more downregulated proteins than upregulated proteins. Noted changes included decreased OprD and PilP, and increased MexEF-OprN, MvaT and Vfr, as well as proteins of ribosome machinery and metabolism clusters. Gene expression analysis confirmed the proteomic data and indicated the downregulation of rpoB and rpoS. In summary, the response to CIP involved approximately a quarter of the proteome, primarily associated with ribosome machinery and metabolic processes. Potential targets for bacterial interference encompassed outer membrane proteins and global regulators, such as MvaT.

Phosphoproteomics Unravel HBV Triggered Rewiring of Host Phosphosignaling Events.

Hepatitis B virus (HBV) infection persists as a major global health problem despite the availability of HBV vaccines for disease prevention. However, vaccination rates remains low in some regions of the world, driving the need for novel strategies to minimise infections and prevent disease progression. Thus, understanding of perturbed molecular signaling events during early phases of HBV infection is required. Phosphosignaling is known to be involved in the HBV infection processes, yet systems-level changes in phosphosignaling pathways in the host during infection remain unclear. To this end, we performed phosphoproteome profiling on HBV-infected HepG2-NTCP cells. Our results showed that HBV infection drastically altered the host phosphoproteome and its associated proteins, including kinases. Computational analysis of this phosphoproteome revealed dysregulation of the pathways involved in immune responses, cell cycle processes, and RNA processing during HBV infection. Kinase Substrate Enrichment Analysis (KSEA) identified the dysregulated activities of important kinases, including those from CMGC (CDK, MAPK, GSK, and CLK), AGC (protein kinase A, G, and C), and TK (Tyrosine Kinase) families. Of note, the inhibition of CLKs significantly reduced HBV infection in HepG2-NTCP cells. In all, our study unravelled the aberrated phosphosignaling pathways and the associated kinases, presenting potential entry points for developing novel therapeutic strategies for HBV treatment.

Asymmetric Electrochemical Catalysis.

Asymmetric electrochemical catalysis, an emerging frontline in asymmetric catalysis and electro-organic synthesis, is summarized. Representative works are classified, with respect to the external chiral resources, including chiral media, chiral mediator, chiral catalyst, and chiral electrode. This concept article is expected to provide readers with the general concepts and perspectives of each chiral electrochemical catalysis mode, and to indicate the potential and future development of asymmetric electrochemical catalysis.

Applications of excipients in the field of 3D printed pharmaceuticals.

The aim of this study was to determine the effect of varying excipient content on the formation and physical properties of 3 D printed tablets. Fifteen different excipient preparations were formed into tablets with radii of 5 mm and thickness of 2 mm, using binder jetting (BJ). The tablets were analyzed by assessing visual and microstructural appearance, friability, hardness, and disintegration time. We found that filling agents with high water solubility (e.g. D-sucrose), binding agents with a high viscosity in solution (e.g. polyethylene glycol 4000) and moistening agent with higher water content can increase the bonding strength and hardness of the 3 D printed tablets and prolonged their disintegration time. This work has demonstrated that the type of excipient and its concentration affects the properties of the 3 D printed tablet. This article may be used as a guide for elucidation of the effects of using conventional tablet excipients in the field of 3 D printed pharmaceuticals. The present work should enable the identification of excipients that satisfy requirements, reduce analysis time, and improve efficiency.

Oral disintegrating patient-tailored tablets of warfarin sodium produced by 3D printing.

Individualized medicine is a new direction in the field of modern pharmacy. In this study, we assessed the feasibility and accuracy of 3D printing techniques for the preparation of individualized doses of mouth-disintegrating tablets of warfarin. Warfarin sodium, D-sucrose, pregelatinized starch, povidone K30, microcrystalline cellulose, and silicon dioxide (at a ratio of 1:42.45:46.15:5.1:4.9:0.4) were mixed and used as the printing powder in the 3D printer; preset parameters were used. The dosage of the tablet was controlled by the number of printing layers. The content, dose uniformity, dose accuracy, hardness, friability, disintegration time, dissolution, and the microstructural and overall appearance were determined to evaluate the printed tablets. For the doses of 3, 2, and 1 mg that were produced in the experiment, the disintegration times were 50.0 ± 5.2, 35.7 ± 4.3, and 11.0 ± 2.2 s, respectively, and the relative errors of the dose were -2.33, -1.50, and 0%, respectively. The other indicators were consistent with the preparation requirements of pharmaceutical tablets. It is possible to prepare tablets with excellent properties and controlled drug doses by using 3D printing techniques. This technology will be an important means to achieve individualized medicine.

Analysis of colorectal cancer glyco-secretome identifies laminin ß-1 (LAMB1) as a potential serological biomarker for colorectal cancer.

The high mortality rate in colorectal cancer is mostly ascribed to metastasis, but the only clinical biomarker available for disease monitoring and prognosis is the carcinoembryonic antigen (CEA). However, the prognostic utility of CEA remains controversial. In an effort to identify novel biomarkers that could be potentially translated for clinical use, we collected the secretomes from the colon adenocarcinoma cell line HCT-116 and its metastatic derivative, E1, using the hollow fiber culture system, and utilized the multilectin affinity chromatography approach to enrich for the secreted glycoproteins (glyco-secretome). The HCT-116 and E1 glyco-secretomes were compared using the label-free quantitative SWATH-MS technology, and a total of 149 glycoproteins were differentially secreted in E1 cells. Among these glycoproteins, laminin ß-1 (LAMB1), a glycoprotein not previously known to be secreted in colorectal cancer cells, was observed to be oversecreted in E1 cells. In addition, we showed that LAMB1 levels were significantly higher in colorectal cancer patient serum samples as compared to healthy controls when measured using ELISA. ROC analyses indicated that LAMB1 performed better than CEA at discriminating between colorectal cancer patients from controls. Moreover, the diagnostic performance was further improved when LAMB1 was used in combination with CEA.

iTRAQ analysis of colorectal cancer cell lines suggests Drebrin (DBN1) is overexpressed during liver metastasis.

Colorectal cancer is currently the third in cancer incidence worldwide and the fourth most common cause of cancer deaths. Mortality in colorectal cancer is often ascribed to liver metastasis. In an effort to elucidate the proteins involved in colorectal cancer liver metastasis, we compared the proteome profiles of the human colon adenocarcinoma cell line HCT-116 with its metastatic derivative E1, using the iTRAQ labelling technology, coupled to 2D-LC and MALDI-TOF/TOF MS. A total of 547 proteins were identified, of which 31 of them were differentially expressed in the E1 cell line. Among these proteins, the differential expressions of translationally controlled tumour protein 1, A-kinase anchor protein 12 and Drebrin (DBN1) were validated using Western blot. In particular, DBN1, a protein not previously known to be involved in colorectal cancer metastasis, was found to be overexpressed in E1 as compared to HCT-116 cells. The overexpression of DBN1 was further validated using immunohistochemistry on colorectal cancer tissue sections with matched lymph node and liver metastasis tissues. DBN1 is currently believed to be involved in actin cytoskeleton reorganisation and suppresses actin filament cross-linking and bundling. Since actin reorganisation is an important process for tumour cell migration and invasion, DBN1 may have an important role during colorectal cancer metastasis.

Sieving through the cancer secretome.

Cancer is among the most prevalent and serious health problems worldwide. Therefore, there is an urgent need for novel cancer biomarkers with high sensitivity and specificity for early detection and management of the disease. The cancer secretome, encompassing all the proteins that are secreted by cancer cells, is a promising source of biomarkers as the secreted proteins are most likely to enter the blood circulation. Moreover, since secreted proteins are responsible for signaling and communication with the tumor microenvironment, studying the cancer secretome would further the understanding of cancer biology. Latest developments in proteomics technologies have significantly advanced the study of the cancer secretome. In this review, we will present an overview of the secretome sample preparation process and summarize the data from recent secretome studies of six common cancers with high mortality (breast, colorectal, gastric, liver, lung and prostate cancers). In particular, we will focus on the various platforms that were employed and discuss the clinical applicability of the key findings in these studies. This article is part of a Special Issue entitled: An Updated Secretome.

A novel multi-task learning network for skin lesion classification based on multi-modal clues and label-level fusion.

In this paper, we propose a multi-task learning (MTL) network based on the label-level fusion of metadata and hand-crafted features by unsupervised clustering to generate new clustering labels as an optimization goal. We propose a MTL module (MTLM) that incorporates an attention mechanism to enable the model to learn more integrated, variable information. We propose a dynamic strategy to adjust the loss weights of different tasks, and trade off the contributions of multiple branches. Instead of feature-level fusion, we propose label-level fusion and combine the results of our proposed MTLM with the results of the image classification network to achieve better lesion prediction on multiple dermatological datasets. We verify the effectiveness of the proposed model by quantitative and qualitative measures. The MTL network using multi-modal clues and label-level fusion can yield the significant performance improvement for skin lesion classification.

A Navigation Algorithm to Enable Sustainable Control of Insect-Computer Hybrid Robot with Stimulus Signal Regulator and Habituation-Breaking Function.

The insect-computer hybrid soft robots are receiving increasing attention due to their excellent motor capabilities, small size, and low power consumption. However, the effective control of insects is limited to minutes since the response from insects is reduced as the number of stimulus signal increase. This phenomenon is known as habituation, which causes the loss of control of robots and hinders their application in practical tasks such as search and rescue missions that require several hours. It has been shown that constantly switching the pattern of stimulus signals can slow down the onset of habituation. Moreover, when habituation occurs, applying a different stimulus signal can break the habituation. Based on this, we have designed a navigation algorithm that can extend the control time of insects to several hours. The algorithm is composed of a stimulation decision-making core responsible for deciding on the type of stimulus signal (left, right, acceleration), a stimulation parameters adjustment (SPA) core responsible for adjusting the stimulus signal voltage constantly to delay the occurrence of habituation, and a reactivation function (RF), as a different stimulus signal from the normal stimulus signal, is used to break insects' habituation to the normal stimulus signal. Experiments have shown that our SPA regulator and RF can significantly extend the control time of insects. Navigation experiments demonstrating effective control of the insects for up to 3 h verified the effectiveness of the navigation algorithm, which strikes a balance between control accuracy and control time.

Robust Reward-Free Actor-Critic for Cooperative Multiagent Reinforcement Learning.

In this article, we consider centralized training and decentralized execution (CTDE) with diverse and private reward functions in cooperative multiagent reinforcement learning (MARL). The main challenge is that an unknown number of agents, whose identities are also unknown, can deliberately generate malicious messages and transmit them to the central controller. We term these malicious actions as Byzantine attacks. First, without Byzantine attacks, we propose a reward-free deep deterministic policy gradient (RF-DDPG) algorithm, in which gradients of agents' critics rather than rewards are sent to the central controller for preserving privacy. Second, to cope with Byzantine attacks, we develop a robust extension of RF-DDPG termed R2F-DDPG, which replaces the vulnerable average aggregation rule with robust ones. We propose a novel class of RL-specific Byzantine attacks that fail conventional robust aggregation rules, motivating the projection-boosted robust aggregation rules for R2F-DDPG. Numerical experiments show that RF-DDPG successfully trains agents to work cooperatively and that R2F-DDPG demonstrates robustness to Byzantine attacks.

Effects of Multiple Ion Reactions Based on a CoSe2 /MXene Cathode in Aluminum-Ion Batteries.

Rechargeable aluminum-ion batteries (RAIBs) have emerged as a promising battery storage technology owing to their cost-effectiveness, operational safety, and high energy density. However, their actual capacity is substantially lower than their true capacity and their cycling stability is poor. Therefore, understanding the energy-storage mechanism may contribute to the successful design of a stable electrode material, on which the performance can be optimized. The aim of this study is to investigate AlCl4 - ions in transition metal cathode materials and mechanisms that enable for their high-energy-storage potential and low Coulombic efficiency. Results of theoretical analysis and experimental verification show that a multi-ion transport mechanism is responsible for the electrochemical behavior of the battery. The lattice distortion of CoSe2 caused by AlCl4 - ion intercalation, has a considerable effect on the initial stability of the battery. MXene as a support material reduces the size of CoSe2 growing on its surface, effectively inhibiting the lattice distortion caused by the interaction with the aluminum-anion complex, thus addressing the issues of poor reversibility, cycle instability, and low Coulombic efficiency of the battery. Hence, understanding the impact of MXene on the battery may aid in further improving the design of electrode materials.

Escherichia coli displays a conserved membrane proteomic response to a range of alcohols.

BACKGROUND: Alcohol is a good and environment-friendly fuel that can be microbially produced, capable of eliminating many of the limitations of the present-day fossil fuels. However, the inherent toxic nature of alcohols to the microbial cells leads to end-product inhibition that limits large-scale alcohol production by fermentation. Fundamental knowledge about the stress responses of microorganisms to alcohols would greatly facilitate to improve the microbial alcohol tolerance. The current study elucidates and compares the changes in the membrane proteome of Escherichia coli in response to a range of alcohols. RESULTS: Although alcohol toxicity increased exponentially with alcohol chain length (2-6 carbon), similar stress responses were observed in the inner and outer membrane proteome of E. coli in the presence of 2-, 4- and 6-carbon alcohols at the MIC50. This pertains to: (1) increased levels of inner membrane transporters for uptake of energy-producing metabolites, (2) reduced levels of non-essential proteins, associated with anaerobic, carbon starvation and osmotic stress, for energy conservation, (3) increased levels of murein degrading enzymes (MltA, EmtA, MliC and DigH) promoting cell elongation and 4) reduced levels of most outer membrane ß-barrel proteins (LptD, FadL, LamB, TolC and BamA). Major outer membrane ß-barrel protein OmpC, which is known to contribute to ethanol tolerance and membrane integrity, was notably reduced by alcohol stress. While LPS is important for OmpC trimerisation, LPS release by EDTA did not lower OmpC levels. This suggests that LPS release, which is reported under alcohol stress, does not contribute to the reduced levels of OmpC in the presence of alcohol. CONCLUSIONS: Since alcohol primarily targets the integrity of the membrane, maintenance of outer membrane OmpC levels in the presence of alcohol might help in the survival of E. coli to higher alcohol concentrations. The study provides important information about the membrane protein responses of E. coli to a range of alcohols, which can be used to develop targeted strategies for increased microbial alcohol tolerance and hence bioalcohol production.

Major Facilitator Superfamily Transporter Participates in the Formation of Dimeric Sorbicillinoids Pigments.

Understanding the biosynthetic pathways of fungal pigments can help elucidate their roles in fungal growth processes. Trichodimerol is a unique cage-like dimeric sorbicillinoids pigment that is commonly isolated from many fungi, however, its biosynthesis is just partially clarified. In this study, we report that a biosynthetic gene cluster encoded major facilitator superfamily transporter (StaE) from the fungus Stagonospora sp. SYSU-MS7888 is involved in the formation of trichodimerol, together with several other dimeric sorbicillinoids. Using Aspergillus oryzae NSARI as a heterologous host, we demonstrated that the formation of dimeric sorbicillinoids required co-expression of the transporter StaE with biosynthetic genes (two PKSs and one monooxygenase) that are responsible for constructing the monomer precursor sorbicillinol. Fluorescence microscopy results showed that eGFP-tagged StaE is localized on the endoplasmic reticulum, suggesting that sorbicillinoid dimerizations might be compartmentalized in this organelle.

Herba Patriniae and its component Isovitexin show anti-colorectal cancer effects by inducing apoptosis and cell-cycle arrest via p53 activation.

Colorectal cancer (CRC) is the most prevalent cancer of the digestive tract. Herba Patriniae (also known as Bai Jiang Cao, HP) have been widely used to manage diarrhea, ulcerative colitis, and several cancers, including CRC. Nonetheless, the molecular mechanisms underlying the pharmacological action of HP on CRC remain unclear. This study investigated the underlying mechanisms of HP against CRC using network pharmacology analysis and in vitro and in vivo experiments. The results revealed nine bioactive compounds of HP. Furthermore, 3460 CRC-related targets of the identified active compounds were predicted from the Gene Expression Omnibus (GEO) database. Furthermore, 65 common targets were identified through the intersection of two related targets. Moreover, ten hub genes, including CDK4, CDK2, CDK1, CCND1, CCNB1, CCNA2, MYC, E2F1, CHEK1, and CDKN1A were identified through the topological analysis. Meanwhile, the GO and KEGG pathway analysis revealed that the core target genes were majorly enriched in the p53 and HIF-1 signaling pathways. Moreover, HP promoted apoptosis and suppressed cell proliferation by activating the p53 signaling pathway in a dose-dependent manner, while a similar effect was observed for Isovitexin (the primary component of HP). Overall, this study provides valuable insights into the underlying mechanisms of HP and its component Isovitexin against CRC, providing a theoretical foundation for additional experimental verification of its clinical application.

CRPN-SFNet: A High-Performance Object Detector on Large-Scale Remote Sensing Images.

Limited by the GPU memory, the current mainstream detectors fail to directly apply to large-scale remote sensing images for object detection. Moreover, the scale range of objects in remote sensing images is much wider than that of general images, which also greatly hinders the existing methods to effectively detect geospatial objects of various scales. For achieving high-performance object detection on large-scale remote sensing images, this article proposes a much faster and more accurate detecting framework, called cropping region proposal network-based scale folding network (CRPN-SFNet). In our framework, the CRPN includes a weak semantic RPN for quickly locating interesting regions and a strategy of generating cropping regions to effectively filter out meaningless regions, which can greatly reduce the computation and storage burden. Meanwhile, the proposed SFNet leverages the scale folding-based training and testing methods to extend the valid detection range of existing detectors, which is beneficial for detecting remote sensing objects of various scales, including very small and very large geospatial objects. Extensive experiments on the public Dataset for Object deTection in Aerial images data set indicate that our CRPN can help our detector deal the larger image faster with the limited GPU memory; meanwhile, the SFNet is beneficial to achieve more accurate detection of geospatial objects with wide-scale range. For large-scale remote sensing images, the proposed detection framework outperforms the state-of-the-art object detection methods in terms of accuracy and speed.

Study on the Hydrogen Embrittlement of Nanograined Materials with Different Grain Sizes by Atomistic Simulation.

Although hydrogen embrittlement (HE) behavior has been extensively studied in bulk materials, little is known about H-related deformation and the fracture of nanograined materials. In this study, H segregation and HE mechanisms of nanograined Fe with different grain sizes are unveiled, following the employment of classical molecular dynamics simulations. The H segregation ratio increased, but the local H concentration at the grain boundaries (GBs) decreased with decreases in the grain size at a given bulk H concentration. The results demonstrate that H atoms increased the yield stress of nanograined models irrespective of the grain size. Furthermore, it is revealed that brittle fractures were inhibited, and the resistance to HE increased as the grain size decreased, due to the fact that the small-grain models had a lower local H concentration at the GBs and an enhanced GB-mediated intergranular deformation. These results are a clear indication of the utility of grain refinement to resist H-induced brittle failure.

Joint optic disc and cup segmentation using feature fusion and attention.

Currently, glaucoma is one of the leading causes of irreversible vision loss. So far, glaucoma is incurable, but early treatment can stop the progression of the condition and slow down the speed and extent of vision loss. Early detection and treatment are crucial to prevent glaucoma from developing into blindness. It is an effective method for glaucoma diagnosis to measure Cup to Disc Ratio (CDR) by the segmentation of Optic Disc (OD) and Optic Cup (OC). Compared with OD segmentation, OC segmentation still faces difficulties in segmentation accuracy. In this paper, a deep learning architecture named FAU-Net (feature fusion and attention U-Net) is proposed for the joint segmentation of OD and OC. It is an improved architecture based on U-Net. By adding a feature fusion module in U-Net, information loss in feature extraction can be reduced. The channel and spatial attention mechanisms are combined to highlight the important features related to the segmentation task and suppress the expression of irrelevant regional features. Finally, a multi-label loss is used to generate the final joint segmentation of OD and OC. Experimental results show that the proposed FAU-Net outperforms the state-of-the-art segmentation of OD and OC on Drishti-GS1, REFUGE, RIM-ONE and ODIR datasets.