Effects of seawater acidification and warming on morphometrics and biomineralization-related gene expression during embryo-larval development of a lightly-calcified echinoderm.

CO2-induced ocean acidification and warming pose ecological threats to marine life, especially calcifying species such as echinoderms, who rely on biomineralization for skeleton formation. However, previous studies on echinoderm calcification amid climate change had a strong bias towards heavily calcified echinoderms, with little research on lightly calcified ones, such as sea cucumbers. Here, we analyzed the embryo-larval development and their biomineralization-related gene expression of a lightly calcified echinoderm, the sea cucumber (Apostichopus japonicus), under experimental seawater acidification (OA) and/or warming (OW). Results showed that OA (- 0.37 units) delayed development and decreased body size (8.58-56.25 % and 0.36-19.66 % decreases in stage duration and body length, respectively), whereas OW (+3.1 °C) accelerated development and increased body size (33.99-55.28 % increase in stage duration and 2.44-14.41 % enlargement in body length). OW buffered the negative effects of OA on the development timing and body size of A. japonicus. Additionally, no target genes were expressed in the blastula stage, and only two biomineralization genes (colp3α, cyp2) and five TFs (erg, tgif, foxN2/3, gata1/2/3, and tbr) were expressed throughout the embryo-larval development. Our findings suggest that the low calcification in A. japonicus larvae may be caused by biomineralization genes contraction, and low expression of those genes. Furthermore, this study indicated that seawater acidification and warming affect expression of biomineralization-related genes, and had an effect on body size and development rate during the embryo-larval stage in sea cucumbers. Our study is a first step toward a better understanding of the complexity of high pCO2 on calcification and helpful for revealing the adaptive strategy of less-calcified echinoderms amid climate change.

The transcriptional response of the Pacific oyster Crassostrea gigas against acute heat stress.

The Pacific oyster, Crassostrea gigas, has evolved sophisticated mechanisms to adapt the changing ambient conditions, and protect themselves from stress-induced injuries. In the present study, the expression profiles of mRNA transcripts in the haemocytes of oysters under heat stress were examined to reveal the possible mechanism of heat stress response. There were 23,315, 23,904, 23,123 and 23,672 transcripts identified in the haemocytes of oysters cultured at 25 °C for 0, 6, 12, and 24 h (designed as B, H6, H12, H24), respectively. And 22,330 differentially expressed transcripts (DTs) were yielded in the pairwise comparisons between the above four samples, which corresponded to 8074 genes. There were 9, 12 and 22 Gene Ontology (GO) terms identified in the DT pairwise comparison groups of H6_B, H12_H6 and H24_H12, respectively, and the richest GO terms in biological process category were cellular catabolic process, translational initiation and apoptotic process, respectively. There were 108, 102 and 102 KEGG pathways successfully retrieved from DTs comparison groups DTH6_B, DTH12_H6 and DTH24_H12, respectively, among which 93 pathways were shared by all three comparison groups, and most of them were related to metabolism of protein, carbohydrate and fat. The expression patterns of 12 representative heat stress response-relevant genes detected by quantitative real-time PCR (qRT-PCR) were similar to those obtained from transcriptome analysis. By flow cytometric analysis, the apoptosis rate of haemocytes increased significantly after oysters were treated at 25 °C for 24 h and recovered at 4 °C for 12 h (p < 0.05) and 36 h (p < 0.01), and it also increased significantly when the heat treatment lasted to 60 h (p < 0.01). The present results indicated that, when oysters encountered short term heat stress, the expression of genes related to energy metabolism, as well as unfolded protein response (UPR) and anti-apoptotic system, were firstly regulated to maintain basic life activities, and then a large number of genes involved in stabilizing protein conformation and facilitating further protein refolding were activated to repair the stress injury. However, the stress injury gradually became irreparable with the stress persisting, and apoptosis was activated when the heat treatment prolonged to 24 h. The information was useful to better understand the molecular mechanism of heat stress response and develop strategies for the improvement of oyster survival rate during summer high-temperature period.

A small heat shock protein (sHSP) from Sinonovacula constricta against heavy metals stresses.

Small heat shock proteins (sHSPs) are ATP-independent molecular chaperones and involved into many physiological and stress processes. In the present study, the full-length cDNA of sHSP was cloned from razor clam Sinonovacula constricta (denoted as ScsHSP) through cDNA library and PCR approaches. Some feature motifs like the typical α-crystalline domain with six beta strands, three susceptible phosphorylation serines (S(15), S(78), and S(82)) were conserved in the deduce amino acid of ScsHSP. Tissue distribution analysis of the ScsHSP revealed that the mRNA transcripts of ScsHSP were constitutively expressed in all examined tissues with the highest expressions in the haemocytes. The temporal expression of ScsHSP in gill and haemocytes after PbCl2 and CdCl2 exposure were recorded by qPCR. The suppressed expression patterns were detected in CdCl2 stress at both tissues, and the minimum expression were detected at 36 h with 0.58-fold decrease in haemocytes and 0.30-fold in gill compared to each control group. During the PbCl2 exposure experiment, the expression level of ScsHSP increased significantly with larger amplitude in haemocytes. As time progressed, the mRNA transcripts of ScsHSP recovered almost to the original level at 36 h. All our results indicated that ScsHSP was involved into mediating environmental pollutants exposure and considered to be a promising candidate bio-mark for heavy metals monitoring.

The link between selenium binding protein from Sinonovacula constricta and environmental pollutions exposure.

Selenium binding proteins (SeBPs) play a crucial role in controlling the oxidation/reduction in many physiological processes. Here we reported the isolation and characterization of a cDNA of SeBP gene from Sinonovacula constricta (denoted as ScSeBP). The full-length cDNA of ScSeBP was of 2345 bp, consisting of a 5'UTR of 246 bp, a 3' UTR of 626 bp, and a complete ORF of 1473 bp encoding a polypeptide with 491 amino acid residues. The predicted molecular mass of deduced amino acid of ScSeBP was 54.85 kDa and the theoretical pI was 6.44. Tissue distribution analysis of the ScSeBP revealed that the mRNA transcripts of ScSeBP were constitutively expressed in all examined tissues with the higher expressions in gill, gonad and the haemocytes. The temporal expression of ScSeBP in gill and haemocytes after B[α]P and heavy metals exposure were recorded by qPCR. B[α]P exposure at 0.5 and 5 mg L(-1) caused significant increase in mRNA expression of ScSeBP in haemocytes, but down-regulated ScSeBP mRNA expression in gill. Concerning heavy metals stresses, the suppressed expression patterns were detected in gill and haemocyte except lower concentration of PbCl2 exposure in haemocytes at 12 h. All our results indicated that ScSeBP was one of key effectors in mediating B[α]P and heavy metals exposure.

Low Latency and Sparse Computing Spiking Neural Networks With Self-Driven Adaptive Threshold Plasticity.

Spiking neural networks (SNNs) have captivated the attention worldwide owing to their compelling advantages in low power consumption, high biological plausibility, and strong robustness. However, the intrinsic latency associated with SNNs during inference poses a significant challenge, impeding their further development and application. This latency is caused by the need for spiking neurons to collect electrical stimuli and generate spikes only when their membrane potential exceeds a firing threshold. Considering the firing threshold plays a crucial role in SNN performance, this article proposes a self-driven adaptive threshold plasticity (SATP) mechanism, wherein neurons autonomously adjust the firing thresholds based on their individual state information using unsupervised learning rules, of which the adjustment is triggered by their own firing events. SATP is based on the principle of maximizing the information contained in the output spike rate distribution of each neuron. This article derives the mathematical expression of SATP and provides extensive experimental results, demonstrating that SATP effectively reduces SNN inference latency, further reduces the computation density while improving computational accuracy, so that SATP facilitates SNN models to be with low latency, sparse computing, and high accuracy.

Fault-Tolerant Attitude Tracking Control Driven by Spiking NNs for Unmanned Aerial Vehicles.

In this article, we proposed a novel fault-tolerant control scheme for quadrotor unmanned aerial vehicles (UAVs) based on spiking neural networks (SNNs), which leverages the inherent features of neural network computing to significantly enhance the reliability and robustness of UAV flight control. Traditional control methods are known to be inadequate in dealing with complex and real-time sensor data, which results in poor performance and reduced robustness in fault-tolerant control. In contrast, the temporal processing, parallelism, and nonlinear capacity of SNNs enable the fault-tolerant control scheme to process vast amounts of sensory data with the ability to accurately identify and respond to faults. Furthermore, SNNs can learn and adjust to new environments and fault conditions, providing effective and adaptive flight control. The proposed SNN-based fault-tolerant control scheme demonstrates significant improvements in control accuracy and robustness compared with conventional methods, indicating its potential applicability and suitability for a range of UAV flight control scenarios.

Pollution characteristics and ecological risk of microplastic in sediments of Liaodong Bay from the northern Bohai Sea in China.

Microplastics (MPs) are widely distributed in marine environments. The pollution characteristics and risk assessment of MPs in estuarine sediments are still insufficient. In this study, the MPs pollution characteristics in surface sediments of the Liao Estuary and Daliao Estuary were investigated. The characteristics of MPs in sediments were determined by stereo microscopy and micro-Fourier transform infrared spectroscopy. The results showed that the average MPs abundance ranged from 32.33 to 49.91 items·kg-1 d.w. The MPs were mainly composed of 500-2000 µm black and blue fibers. Five polymer types were identified, including rayon (RA) (87.46 %), polyethylene terephthalate (PET) (6.81 %), polyamide (PA) (2.94 %), polypropylene (PP) (2.17 %) and polyethylene (PE) (0.62 %). The pollution load index (PLI) risk assessment showed that all sampling sites were at Hazard Level I. Our results can provide useful information for assessing the environmental risks of MPs in coastal areas of China.

Neuroadaptive Tracking Control of Affine Nonlinear Systems Using Echo State Networks Embedded With Multiclustered Structure and Intrinsic Plasticity.

In this article, we present an echo state network (ESN)-based tracking control approach for a class of affine nonlinear systems. Different from the most existing neural-network (NN)-based control methods that are focused on the feedforward NN, the proposed method adopts a bioinspired recurrent NN fusing with multiple cluster and intrinsic plasticity (IP) to deal with modeling uncertainties and coupling nonlinearities in the systems. The key features of this work can be summarized as follows: 1) the proposed control is built upon the ESN embedded with multiclustered reservoir inspired from the hierarchically clustered organizations of cortical connections in mammalian brains; 2) the developed neuroadaptive control scheme utilizes unsupervised learning rules inspired from the neural plasticity mechanism of the individual neuron in nervous systems, called IP; 3) a multiclustered reservoir with IP is integrated into the algorithm to enhance the approximation performance of NN; and 4) the multiclustered reservoir is constructed offline and is task-independent, rendering the proposed method less expensive in computation. The effectiveness of the method is also confirmed by comparison with the existing neuroadaptive methods via numerical simulations, demonstrating that better tracking precision is achieved by the proposed method.

Event-Driven Intrinsic Plasticity for Spiking Convolutional Neural Networks.

The biologically discovered intrinsic plasticity (IP) learning rule, which changes the intrinsic excitability of an individual neuron by adaptively turning the firing threshold, has been shown to be crucial for efficient information processing. However, this learning rule needs extra time for updating operations at each step, causing extra energy consumption and reducing the computational efficiency. The event-driven or spike-based coding strategy of spiking neural networks (SNNs), i.e., neurons will only be active if driven by continuous spiking trains, employs all-or-none pulses (spikes) to transmit information, contributing to sparseness in neuron activations. In this article, we propose two event-driven IP learning rules, namely, input-driven and self-driven IP, based on basic IP learning. Input-driven means that IP updating occurs only when the neuron receives spiking inputs from its presynaptic neurons, whereas self-driven means that IP updating only occurs when the neuron generates a spike. A spiking convolutional neural network (SCNN) is developed based on the ANN2SNN conversion method, i.e., converting a well-trained rate-based artificial neural network to an SNN via directly mapping the connection weights. By comparing the computational performance of SCNNs with different IP rules on the recognition of MNIST, FashionMNIST, Cifar10, and SVHN datasets, we demonstrate that the two event-based IP rules can remarkably reduce IP updating operations, contributing to sparse computations and accelerating the recognition process. This work may give insights into the modeling of brain-inspired SNNs for low-power applications.

Robust clothing-independent gait recognition using hybrid part-based gait features.

Recently, gait has been gathering extensive interest for the non-fungible position in applications. Although various methods have been proposed for gait recognition, most of them can only attain an excellent recognition performance when the probe and gallery gaits are in a similar condition. Once external factors (e.g., clothing variations) influence people's gaits and changes happen in human appearances, a significant performance degradation occurs. Hence, in our article, a robust hybrid part-based spatio-temporal feature learning method is proposed for gait recognition to handle this cloth-changing problem. First, human bodies are segmented into the affected and non/less unaffected parts based on the anatomical studies. Then, a well-designed network is proposed in our method to formulate our required hybrid features from the non/less unaffected body parts. This network contains three sub-networks, aiming to generate features independently. Each sub-network emphasizes individual aspects of gait, hence an effective hybrid gait feature can be created through their concatenation. In addition, temporal information can be used as complement to enhance the recognition performance, a sub-network is specifically proposed to establish the temporal relationship between consecutive short-range frames. Also, since local features are more discriminative than global features in gait recognition, in this network a sub-network is specifically proposed to generate features of local refined differences. The effectiveness of our proposed method has been evaluated by experiments on the CASIA Gait Dataset B and OU-ISIR Treadmill Gait Dataset B. Related experiments illustrate that compared with other gait recognition methods, our proposed method can achieve a prominent result when handling this cloth-changing gait recognition problem.

Dual molecular light switches for pH and DNA based on a novel Ru(II) complex. A non-intercalating Ru(II) complex for DNA molecular light switch.

A new Ru(II) complex of [Ru(phen)(2)(Hcdpq)](ClO(4))(2) {phen = 1,10-phenanthroline, Hcdpq = 2-carboxyldipyrido[3,2-f:2',3'-h]quinoxaline} was synthesized and characterized. The spectrophotometric pH and calf thymus DNA (ct-DNA) titrations showed that the complex acted as a dual molecular light switch for pH and ct-DNA with emission enhancement factors of 17 and 26, respectively. It was shown to be capable of distinguishing ct-DNA from yeast RNA with this binding selectivity being superior to two well-known DNA molecular light switches of [Ru(bpy)(2)(dppz)](2+) {bpy =2,2'-bipyridine, and dppz = dipyrido-[3,2-a:2',3'-c]phenazine}and ethidium bromide. The complex bond to ct-DNA probably in groove mode with a binding constant of (4.67 ± 0.06) × 10(3) M(-1) in 5 mM Tris-HCl, 50 mM NaCl (pH = 7.10) buffer solution, as evidenced by UV-visible absorption and luminescence titrations, the dependence of DNA binding constants on NaCl concentrations, DNA competitive binding with ethidium bromide, and emission lifetime and viscosity measurements. To get insight into the light-switch mechanism, theoretical calculations were also performed by applying density functional theory (DFT) and time-dependent DFT.

Intrinsic Plasticity-Based Neuroadptive Control With Both Weights and Excitability Tuning.

This brief presents an intrinsic plasticity (IP)-driven neural-network-based tracking control approach for a class of nonlinear uncertain systems. Inspired by the neural plasticity mechanism of individual neuron in nervous systems, a learning rule referred to as IP is employed for adjusting the radial basis functions (RBFs), resulting in a neural network (NN) with both weights and excitability tuning, based on which neuroadaptive tracking control algorithms for multiple-input-multiple-output (MIMO) uncertain systems are derived. Both theoretical analysis and numerical simulation confirm the effectiveness of the proposed method.

Distinct microbiota assembly mechanisms revealed in different reconstruction stages during gut regeneration in the sea cucumber Apostichopus japonicus.

Apostichopus japonicus is a useful model for studying organ regeneration, and the gut microbiota is important for host organ regeneration. However, the reconstruction process and the mechanisms of gut microbiota assembly during gut regeneration in sea cucumbers have not been well studied. In the present study, gut regeneration was induced (via evisceration) in A. japonicus, and gut immune responses and bacterial diversity were investigated to reveal gut microbiota assembly and its possible mechanisms during gut regeneration. The results revealed that bacterial community reconstruction involved two stages with distinct assembly mechanisms, where the reconstructed community was initiated from the bacterial consortium in the residual digestive tract and tended to form a novel microbiota in the later stage of reconstruction. Together, the results of immunoenzyme assays, community phylogenetic analysis, and source tracking suggested that the host deterministic process was stronger in the initial stage than in the later stage. The bacterial interactions that occurred were significantly different between the two stages. Positive interactions dominated in the initial stage, while more complex and competitive interactions developed in the later stage. Such a dynamic bacterial community could provide the host with energetic and immune benefits that promote gut regeneration and functional recovery. The results of the present study provide insights into the processes and mechanisms of gut microbiota assembly during intestinal regeneration that are valuable for understanding gut regeneration mechanisms mediated by the microbiota.

Expression profile of a novel glutathione S-transferase gene in the marine polychaete Perinereis aibuhitensis in short-term responses to phenanthrene, fluoranthene, and benzo[α]pyrene.

Polychaete worms can eliminate polycyclic aromatic hydrocarbons (PAHs) in environments through a mechanism that increases their water solubility. This detoxification starts with cytochrome P450 enzymes (CYPs) and then with glutathione S-transferases (GSTs). Here, a novel GST gene was identified and characterized from the widespread polychaete Perinereis aibuhitensis. The full-length cDNA of GST is 1544 bp and encodes 256 amino acids, belonging to the omega class. Gene expression patterns in P. aibuhitensis showed that its transcriptional level was positively correlated with the concentration of benzo[α]pyrene (0.5, 2, 4, and 8 µg/L) exposure but was negatively correlated with a PAH benzene ring after it was exposed to the same mass concentrations of fluoranthene (3.2 µg/L), phenanthrene (2.9 µg/L), and benzo[α]pyrene (4.0 µg/L) during the 14-day experimentation. These findings indicate that omega GST may play an important role in the phase II detoxification of PAHs in polychaete worms, and the persistence and bioavailability of PAHs may depend on benzene rings.

A triphenylamine-grafted imidazo[4,5-f][1,10]phenanthroline ruthenium(II) complex: acid-base and photoelectric properties.

A new heteroleptic ruthenium(II) complex of [Ru(Hipdpa)(Hdcbpy)(NCS)(2)](-).0.5H(+).0.5[N(C(4)H(9))(4)](+) Ru(Hipdpa) {where Hdcbpy = monodeprotonated 4,4'-dicarboxy-2,2'-bipyridine and Hipdpa = 4-(1H-imidazo[4,5-f][1,10]phenanthrolin-2-yl)-N,N-diphenylaniline} was synthesized and characterized by elementary analysis, standard spectroscopy techniques, and cyclic voltammetry. The ground- and excited-state acid-base properties of Ru(Hipdpa) were studied by means of UV-vis absorption spectrophotometric and spectrofluorimetric titrations in 4:1(v/v) Britton-Robinson/dimethylformamide buffer solution. The four-step separate protonation/deprotonation processes were found in the ground states, and one of which taking place near the physiological pH range. The two observable excited-state protonation/deprotonation processes were found for the Ru(Hipdpa), constituting pH-induced "off-on-off" emission switches. The performance of the complexes as photosensitizers in nanocrystalline TiO(2)-based liquid solar cells containing an electrolyte solution (0.05 M I(2), 0.5 M LiI, and 0.5 M 4-tert-butylpyridine in 50% acetonitrile and 50% propylene carbonate) was investigated and found to achieve a much improved device performance (a short-circuit photocurrent density of 18.7 mA cm(-2), an open-circuit voltage of 630 mV, and an overall conversion efficiency of 6.85%) compared to a triphenylamine-free parent complex [Ru(Hpip)(Hdcbpy)(NCS)(2)](-).[N(C(4)H(9))(4)](+)-based device {Hpip = 2-phenyl-1H-imidazo[4,5-f][1,10]phenanthroline} and a comparable performance to that of cis-bis(isothiocyanato)bis(2,2'-bipyridine-4,4'-dicarboxylic acid)ruthenium(II) (N3) under identical experimental conditions. A density functional theory calculation of the molecular structures and electronic properties of the complexes was also carried out in an effort to understand their effectiveness in TiO(2)-based solar cells.

Chaotic time series prediction using phase space reconstruction based conceptor network.

The Conceptor network is a new framework of reservoir computing (RC), in addition to the features of easy training, global convergence, it can online learn new classes of input patterns without complete re-learning from all the training data. The conventional connection topology and weights of the hidden layer (reservoir) of RC are initialized randomly, and are fixed to be no longer fine-tuned after initialization. However, it has been demonstrated that the reservoir connection of RC plays an important role in the computational performance of RC. Therefore, in this paper, we optimize the Conceptor's reservoir connection and propose a phase space reconstruction (PSR) -based reservoir generation method. We tested the generation method on time series prediction task, and the experiment results showed that the proposed PSR-based method can improve the prediction accuracy of Conceptor networks. Further, we compared the PSR-based Conceptor with two Conceptor networks of other typical reservoir topologies (random connected, cortex-like connected), and found that all of their prediction accuracy showed a nonlinear decline trend with increasing storage load, but in comparison, our proposed PSR-based method has the best accuracy under different storage loads.

DNA groove-binding and acid-base properties of a Ru(II) complex containing anthryl moieties.

DNA groove binders have been poorly studied as compared to the intercalators. A novel Ru(II) complex of [Ru(aeip)2(Haip)](PF6)2 {Haip = 2-(9-anthryl)-1H-imidazo[4,5-f][1,10]phenanthroline and aeip = 2-(anthracen-9-yl)-1-ethyl-imidazo[4,5-f][1, 10]phenanthroline} is synthesized and characterized by elemental analysis, 1H NMR spectroscopy and mass spectrometry. The complex is evidenced to be a calf-thymus DNA groove binder with a large intrinsic binding constant of 106 M-1 order of magnitude as supported by UV-visible absorption spectral titrations, salt effects, DNA competitive binding with ethidium bromide, DNA melting experiment, DNA viscosity measurements and density functional theory calculations. The acid-base properties of the complex studied by UV-Vis spectrophotometric titrations are reported as well.

Distribution patterns and ecological risk of endocrine-disrupting chemicals at Qingduizi Bay (China): A preliminary survey in a developing maricultured bay.

The occurrence and estrogenic activities of seven phenolic endocrine-disrupting chemical (EDC) compounds (nonylphenol (NP), octylphenol (4-OP), 2,4-dichlorophenol (2,4-DCP), 4-tertbutylphenol (4-t-BP), 4-tert-octylphenol (4-t-OP), tetrabromobisphenol A (TBBPA), and bisphenol A (BPA)) in the sediments of Qingduizi Bay (NorthernYellow Sea, China) in superficial sediments were investigated to evaluate their potential ecological impacts on the health of aquaculture organisms. All compounds, except 4-OP and 4-t-BP, were recorded in most sampling sites (1.06-28.07 ng g-1 dw in maricultural ponds (MPs), 1.98-8.22 ng g-1 dw in outer bay (OB)). BPA and 4-t-OP were the predominant EDC compounds in MPs and OB, respectively. Correlation between BPA and 4-t-OP indicated these compounds may share a similar source or pathway. Analyzed estrogenic activity revealed a low risk of total EDCs. The ranking of risk quotient showed 4-t-OP posed a median risk and TBBPA posed a high risk to the aquatic ecosystem.

A DM9-containing protein from oyster Crassostrea gigas (CgDM9CP-2) serves as a multipotent pattern recognition receptor.

DM9 is a novel protein domain with unknown function originally discovered in Drosophila melanogaster. Recently, a protein harboring DM9 repeats was identified as mannose-specific lectin (CgCGL1, renamed as CgDM9CP-1) from the Pacific oyster Crassostrea gigas. In the present study, another DM9 containing protein was identified from oyster C. gigas (designated as CgDM9CP-2). The open reading frame of CgDM9CP-2 gene was of 432 bp, encoding a polypeptide of 143 amino acids with two tandem DM9 repeats. The deduced amino acid sequence of CgDM9CP-2 shared 60.8% identity with that of CgDM9CP-1. In the unrooted phylogenetic tree, CgDM9CP-2 was closely clustered with CgDM9CP-1, and then assigned into the branch of invertebrate DM9CPs. The mRNA transcripts of CgDM9CP-2 were expressed in all the tested tissues, including mantle, gonad, gills, adductor muscle, hemocytes, and hepatopancreas, with the highest expression level in gills. CgDM9CP-2 protein was mainly distributed on the cytomembrane of oyster hemocytes. After mannose stimulation, the mRNA expression of CgDM9CP-2 in gills was up-regulated to the peak level (5.90-fold of that in SSW group, p < 0.05) at 24 h, and kept at a significantly higher level compared with that in control group at 6-48 h. It significantly increased at 6 h (2.33-fold, p < 0.05), and 12 h (3.08-fold, p < 0.05) post Vibrio splendidus stimulation, and then gradually decreased from 48 to 72 h (p < 0.05) with significant difference comparing with that in control group. The recombinant CgDM9CP-2 protein (rCgDM9CP-2) displayed higher binding affinity to D-(+)-mannose while lower binding affinity to lipopolysaccharide and peptidoglycan. rCgDM9CP-2 also exhibited binding activity towards fungi (Pichia pastoris and Yarrowia lipolytica), gram-positive bacteria (Staphylococcus aureus and Micrococcus luteus), and gram-negative bacteria (Escherichia coli, Vibrio anguillarum, Aeromonas hydrophila and V. splendidus). It could agglutinate fungi P. pastoris and Y. lipolytica, and inhibit the growth of P. pastoris, S. aureus, V. anguillarum, and V. splendidus. These results collectively indicated that CgDM9CP-2 not only served as a pattern recognition receptor with a broad range of recognition spectrum, but also involved in inhibiting the growth of invading microbe in the innate immune response of oyster, which would provide further evidence for the function of DM9 domain in the innate immune system.