Purification and Characterization of a Novel Fibrinolytic Enzyme from Marine Bacterium Bacillus sp. S-3685 Isolated from the South China Sea.

A novel fibrinolytic enzyme, BSFE1, was isolated from the marine bacterium Bacillus sp. S-3685 (GenBank No.: KJ023685) found in the South China Sea. This enzyme, with a molecular weight of approximately 42 kDa and a specific activity of 736.4 U/mg, exhibited its highest activity at 37 °C in a phosphate buffer at pH 8.0. The fibrinolytic enzyme remained stable over a pH range of 7.5 to 10.0 and retained about 76% of its activity after being incubated at 37 °C for 2 h. The Km and Vmax values of the enzyme at 37 °C were determined to be 2.1 µM and 49.0 µmol min-1 mg-1, respectively. The fibrinolytic activity of BSFE1 was enhanced by Na+, Ba2+, K+, Co2+, Mn2+, Al3+, and Cu2+, while it was inhibited by Fe3+, Ca2+, Mg2+, Zn2+, and Fe2+. These findings indicate that the fibrinolytic enzyme isolated in this study exhibits a strong affinity for fibrin. Moreover, the enzyme we have purified demonstrates thrombolytic enzymatic activity. These characteristics make BSFE1 a promising candidate for thrombolytic therapy. In conclusion, the results obtained from this study suggest that our work holds potential in the development of agents for thrombolytic treatment.

Laser Precise Synthesis of Oxidation-Free High-Entropy Alloy Nanoparticle Libraries.

High-entropy alloy nanoparticles (HEA-NPs) show exceptional properties and great potential as a new generation of functional materials, yet a universal and facile synthetic strategy in air toward nonoxidized and precisely controlled composition remains a huge challenge. Here we provide a laser scribing method to prepare single-phase solid solution HEA-NPs libraries in air with tunable composition at the atomic level, taking advantage of the laser-induced metastable thermodynamics and substrate-assisted confinement effect. The three-dimensional porous graphene substrate functions as a microreactor during the fast heating/cooling process, which is conductive to the generation of the pure alloy phase by effectively blocking the binding of oxygen and metals, but is also beneficial for realizing accurate composition control via microstructure confinement-endowed favorable vapor pressure. Furthermore, by combining an active learning approach based on an adaptive design strategy, we discover an optimal composition of quinary HEA-NP catalysts with an ultralow overpotential for Li-CO2 batteries. This method provides a simple, fast, and universal in-air route toward the controllable synthesis of HEA-NPs, potentially integrated with machine learning to accelerate the research on HEAs.

Comparative Study on Enzymatic Characteristics of Two κ-Carrageenases from Carrageenan-Degrading Bacterium Catenovulum agarivorans DS2.

κ-Carrageenase plays an important role in achieving the high-value utilization of carrageenan. Factors such as the reaction temperature, thermal stability, catalytic efficiency, and product composition are key considerations for its large-scale application. Previous studies have shown that the C-terminal noncatalytic domains (nonCDs) could influence the enzymatic properties, of κ-carrageenases, providing a strategy for exploring κ-carrageenases with different properties, especially catalytic products. Accordingly, two κ-carrageenases (CaKC16A and CaKC16B), from the Catenovulum agarivorans DS2, were selected and further characterized. Bioinformatics analysis suggested that CaKC16A contained a nonCD but CaKC16B did not. CaKC16A exhibited better enzymatic properties than CaKC16B, including thermal stability, substrate affinity, and catalytic efficiency. After truncation of the nonCD of CaKC16A, its thermal stability, substrate affinity, and catalytic efficiency have significantly decreased, indicating the vital role of nonCD in maintaining a good enzymatic property. Moreover, CaKC16A degraded κ-carrageenan to produce a highly single κ-neocarratetrose, while CaKC16B produced a single κ-neocarrabiose. CaKC16A could degrade ß/κ-carrageenan to produce a highly single desulfated κ-neocarrahexaose, while CaKC16B produced κ-neocarrabiose and desulfated κ-neocarratetrose. Furthermore, it was proposed that CaKC16A and CaKC16B participate in the B/KC metabolic pathway and serve different roles, providing new insight into obtaining κ-carrageenases with different properties.

Biochemical Characterization of a Heat-Resistant κ-Carrageenase Capable of Tolerating High Temperatures up to 100 °C.

κ-Carrageenase plays a crucial role in the high-value utilization of carrageenan. Heat resistance is a key factor in the practical application of κ-carrageenase, as carrageenan exhibits gel-like properties. Previous studies have shown that the C-terminal noncatalytic domains (nonCDs) can affect the thermostability of κ-carrageenases. In this study, we expressed and characterized a κ-carrageenase, MtKC16A, which contains three nonCDs, from Microbulbifer thermotolerans. MtKC16A has the highest activity at 80 °C and pH 7.0. Surprisingly, it exhibits excellent heat resistance, with 71.58% relative activity at 100 °C and still retains over 50% residual activity after incubation at 100 °C for 60 min. Additionally, MtKC16A has been shown to have a dual substrate hydrolysis activity. It can degrade κ-carrageenan to produce highly single Nκ4 and degrade ß/κ-carrageenan to produce Nκ2 and desulfated Nκ4 DA-G-DA-G4S, suggesting its potential in producing κ- and ß/κ-hybrid oligosaccharides. Furthermore, we found that the unknown function domain (UNFD) in MtKC16A plays the most vital role among the three nonCDs. When this UNFD is truncated, the resulting mutants completely lose their catalytic ability at 100 °C. Finally, by introducing this UNFD to the C-terminal of another κ-carrageenase CaKC16B, we were able to improve its heat resistance at 100 °C.

Systematic review on carrageenolytic enzymes: From metabolic pathways to applications in biotechnology.

Carrageenan, the major carbohydrate component of some red algae, is an important renewable bioresource with very large annual outputs. Different types of carrageenolytic enzymes in the carrageenan metabolic pathway are potentially valuable for the production of carrageenan oligosaccharides, biofuel, and other chemicals obtained from carrageenan. However, these enzymes are not well-developed for oligosaccharide or biofuel production. For further application, comprehensive knowledge of carrageenolytic enzymes is essential. Therefore, in this review, we first summarize various carrageenolytic enzymes, including the recently discovered ß-carrageenase, carrageenan-specific sulfatase, exo-α-3,6-anhydro-D-galactosidase (D-ADAGase), and exo-ß-galactosidase (BGase), and describe their enzymatic characteristics. Subsequently, the carrageenan metabolic pathways are systematically presented and applications of carrageenases and carrageenan oligosaccharides are illustrated with examples. Finally, this paper discusses critical aspects that can aid researchers in constructing cascade catalytic systems and engineered microorganisms to efficiently produce carrageenan oligosaccharides or other value-added chemicals through the degradation of carrageenan. Overall, this paper offers a comprehensive overview of carrageenolytic enzymes, providing valuable insights for further exploration and application of these enzymes.

Green moisture-electric generator based on supramolecular hydrogel with tens of milliamp electricity toward practical applications.

Moisture-electric generators (MEGs) has emerged as promising green technology to achieve carbon neutrality in next-generation energy suppliers, especially combined with ecofriendly materials. Hitherto, challenges remain for MEGs as direct power source in practical applications due to low and intermittent electric output. Here we design a green MEG with high direct-current electricity by introducing polyvinyl alcohol-sodium alginate-based supramolecular hydrogel as active material. A single unit can generate an improved power density of ca. 0.11 mW cm-2, a milliamp-scale short-circuit current density of ca. 1.31 mA cm-2 and an open-circuit voltage of ca. 1.30 V. Such excellent electricity is mainly attributed to enhanced moisture absorption and remained water gradient to initiate ample ions transport within hydrogel by theoretical calculation and experiments. Notably, an enlarged current of ca. 65 mA is achieved by a parallel-integrated MEG bank. The scalable MEGs can directly power many commercial electronics in real-life scenarios, such as charging smart watch, illuminating a household bulb, driving a digital clock for one month. This work provides new insight into constructing green, high-performance and scalable energy source for Internet-of-Things and wearable applications.

[A multi-center epidemiological study on pneumococcal meningitis in children from 2019 to 2020]. / 2019­2020å¹´160ä¾‹å„¿ç«¥è‚ºç‚Žé“¾çƒèŒè„‘è†œç‚Žä¸´åºŠæµè¡Œç— å­¦å¤šä¸­å¿ƒç ”ç©¶.

OBJECTIVES: To investigate the clinical characteristics and prognosis of pneumococcal meningitis (PM), and drug sensitivity of Streptococcus pneumoniae (SP) isolates in Chinese children. METHODS: A retrospective analysis was conducted on clinical information, laboratory data, and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country. RESULTS: Among the 160 children with PM, there were 103 males and 57 females. The age ranged from 15 days to 15 years, with 109 cases (68.1%) aged 3 months to under 3 years. SP strains were isolated from 95 cases (59.4%) in cerebrospinal fluid cultures and from 57 cases (35.6%) in blood cultures. The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87) and 27% (21/78), respectively. Fifty-five cases (34.4%) had one or more risk factors for purulent meningitis, 113 cases (70.6%) had one or more extra-cranial infectious foci, and 18 cases (11.3%) had underlying diseases. The most common clinical symptoms were fever (147 cases, 91.9%), followed by lethargy (98 cases, 61.3%) and vomiting (61 cases, 38.1%). Sixty-nine cases (43.1%) experienced intracranial complications during hospitalization, with subdural effusion and/or empyema being the most common complication [43 cases (26.9%)], followed by hydrocephalus in 24 cases (15.0%), brain abscess in 23 cases (14.4%), and cerebral hemorrhage in 8 cases (5.0%). Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old, with rates of 91% (39/43) and 83% (20/24), respectively. SP strains exhibited complete sensitivity to vancomycin (100%, 75/75), linezolid (100%, 56/56), and meropenem (100%, 6/6). High sensitivity rates were also observed for levofloxacin (81%, 22/27), moxifloxacin (82%, 14/17), rifampicin (96%, 25/26), and chloramphenicol (91%, 21/23). However, low sensitivity rates were found for penicillin (16%, 11/68) and clindamycin (6%, 1/17), and SP strains were completely resistant to erythromycin (100%, 31/31). The rates of discharge with cure and improvement were 22.5% (36/160) and 66.2% (106/160), respectively, while 18 cases (11.3%) had adverse outcomes. CONCLUSIONS: Pediatric PM is more common in children aged 3 months to under 3 years. Intracranial complications are more frequently observed in children under 1 year old. Fever is the most common clinical manifestation of PM, and subdural effusion/emphysema and hydrocephalus are the most frequent complications. Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates. Adverse outcomes can be noted in more than 10% of PM cases. SP strains are high sensitivity to vancomycin, linezolid, meropenem, levofloxacin, moxifloxacin, rifampicin, and chloramphenicol.

Microfluidic Chip-Assisted Upconversion Luminescence Biosensing Platform for Point-of-Care Virus Diagnostics.

Epidemics caused by multiple viruses continue to emerge, which have brought a terrible impact on human society. Identification of viral infections with high sensitivity and portability is of significant importance for the screening and management of diseases caused by viruses. Herein, a microfluidic chip (MFC)-assisted upconversion luminescence biosensing platform is designed and fabricated for point-of-care virus detection. Upconversion nanoparticles with excellent stability are successfully synthesized as luminescent agents for optical signal generation in the portable virus diagnostic platform. The relevant investigation results illustrate that the MFC-assisted virus diagnostic platform possesses outstanding performance such as good integration, high sensitivity (1.12 pg mL-1), ease of use, and portability. In addition, clinical sample test result verifies its more prominent virus diagnostic properties than commercially available rapid test strips. All of these thrilling capabilities imply that the designed portable virus diagnostic platform has great potential for future virus detection applications.

Perovskite Nanocrystals Induced Core-Shell Inorganic-Organic Nanofibers for Efficient Energy Harvesting and Self-Powered Monitoring.

The emerging field of wearable electronics requires power sources that are flexible, lightweight, high-capacity, durable, and comfortable for daily use, which enables extensive use in electronic skins, self-powered sensing, and physiological health monitoring. In this work, we developed the core-shell and biocompatible Cs2InCl5(H2O)@PVDF-HFP nanofibers (CIC@HFP NFs) by one-step electrospinning assisted self-assembly method for triboelectric nanogenerators (TENGs). By adopting lead-free Cs2InCl5(H2O) as an inducer, CIC@HFP NFs exhibited ß-phase-enhanced and self-aligned nanocrystals within the uniaxial direction. The interface interaction was further investigated by experimental measurements and molecular dynamics, which revealed that the hydrogen bonds between Cs2InCl5(H2O) and PVDF-HFP induced automatically well-aligned dipoles and stabilized the ß-phase in the CIC@HFP NFs. The TENG fabricated using CIC@HFP NFs and nylon-6,6 NFs exhibited significant improvement in output voltage (681 V), output current (53.1 µA) and peak power density (6.94 W m-2), with the highest reported output performance among TENGs based on halide-perovskites. The energy harvesting and self-powered monitoring performance were further substantiated by human motions, showcasing its ability to charge capacitors and effectively operate electronics such as commercial LEDs, stopwatches, and calculators, demonstrating its promising application in biomechanical energy harvesting and self-powered sensing.

A rapid one-step affinity purification of C-phycocyanin from Spirulina platensis.

The high-purity phycocyanin has a high commercial value. Most current purification methods of C-phycocyanin involve multiple steps, which are complicated and time-consuming. To solve the problem, this research was studied, and an efficient affinity chromatography purification for C-phycocyanin from Spirulina platensis was developed. Through molecular docking simulation, virtual screening of ligands was performed, and ursolic acid was identified as the specific affinity ligand, which coupled to Affi-Gel 102 gel via 1-ethyl (3-dimethylaminopropyl)-3-carbodiimide, hydrochloride as coupling agent. With this customized and synthesized resin, a high-efficiency one-step purification procedure for C-phycocyanin was developed and optimized, the purity was determined to be 4.53, and the yield was 69 %. This one-step purification protocol provides a new approach for purifying other phycobilin proteins.

Effective social spider optimization algorithms for distributed assembly permutation flowshop scheduling problem in automobile manufacturing supply chain.

This paper presents a novel distributed assembly permutation flowshop scheduling problem (DAPFSP) based on practical problems in automobile production. Different from the existing research on DAPFSP, this study considers that each component of the final product is composed of more than one part. Components are processed in a set of identical components manufacturing factories and are assembled into products in the assembly factory. The integration of manufacturing processes is an important objective of Industry 4.0. For solving this problem with the minimum makespan criterion, we introduce a three-level representation and a novel initialization method. To enhance the search ability of the proposed algorithms, we design three local search methods and two restart procedures according to characteristics of the problem. Then, by incorporating the problem specific knowledge with the social spider optimization algorithm (SSO), we propose three SSO variants: the SSO with hybrid local search strategies (HSSO), the HSSO with restart procedures (HSSOR), and the HSSOR with self-adaptive selection probability (HSSORP). Finally, 810 extended instances based on the famous instances are used to test the proposed algorithms. In most cases, HSSOR performs the best, with an average comparison metric value of 0.158% across three termination conditions, while the average comparison metric value for the best comparison method is 2.446%, which is 15.481 times that of HSSOR. Numerical results demonstrate that the proposed algorithms can solve the problem efficiently.

Improving long-term multivariate time series forecasting with a seasonal-trend decomposition-based 2-dimensional temporal convolution dense network.

Improving the accuracy of long-term multivariate time series forecasting is important for practical applications. Various Transformer-based solutions emerging for time series forecasting. Recently, some studies have verified that the most Transformer-based methods are outperformed by simple linear models in long-term multivariate time series forecasting. However, these methods have some limitations in exploring complex interdependencies among various subseries in multivariate time series. They also fall short in leveraging the temporal features of the data sequences effectively, such as seasonality and trends. In this study, we propose a novel seasonal-trend decomposition-based 2-dimensional temporal convolution dense network (STL-2DTCDN) to deal with these issues. We incorporate the seasonal-trend decomposition based on loess (STL) to explore the trend and seasonal features of the original data. Particularly, a 2-dimensional temporal convolution dense network (2DTCDN) is designed to capture complex interdependencies among various time series in multivariate time series. To evaluate our approach, we conduct experiments on six datasets. The results demonstrate that STL-2DTCDN outperforms existing methods in long-term multivariate time series forecasting.

Magnetic-responsive upconversion luminescence resonance energy transfer (LRET) biosensor for ultrasensitive detection of SARS-CoV-2 spike protein.

Upconversion nanoparticles (UCNPs) are ideal donors for luminescence resonance energy transfer (LRET)-based biosensors due to their excellent upconversion luminescence properties. However, the relatively large size of antibodies and proteins limits the application of UCNPs-based LRET biosensors in protein detection because the large steric hindrance of proteins leads to low energy transfer efficiency between UCNPs and receptors. Herein, we developed a magnetic responsive UCNPs-based LRET biosensor to control the coupling distance between antibody-functionalized UCNPs (Ab-UCNPs) as donors and antibody-PEG linker-magnetic gold nanoparticles (Ab-PEG-MGNs) as acceptors for ultrasensitive and highly selective detection of SARS-CoV-2 spike proteins. Our results showed that this platform reversibly shortened the coupling distance between UCNPs and MGNs and enhanced the LRET signal with a 10-fold increase in the limit of detection (LOD) from 20.6 pg/mL without magnetic modulation to 2.1 pg/mL with magnetic modulation within 1 h. The finite-difference time-domain (FDTD) simulation with cyclic distance change confirmed the distance-dependent LRET efficiency under magnetic modulation, which supported the experimental results. Moreover, the applications of this magnetic-responsive UCNP-based LRET biosensor could be extended to other large-size biomolecule detection.

Direct observation of intrinsic room-temperature ferroelectricity in 2D layered CuCrP2S6.

Multiferroic materials have ignited enormous interest owing to their co-existence of ferroelectricity and ferromagnetism, which hold substantial promise for advanced device applications. However, the size effect, dangling bonds, and interface effect in traditional multiferroics severely hinder their potential in nanoscale device applications. Recent theoretical and experimental studies have evidenced the possibility of realizing two-dimensional (2D) multiferroicity in van der Waals (vdW) layered CuCrP2S6. However, the incorporation of magnetic Cr ions in the ferroelectric framework leads to antiferroelectric and antiferromagnetic orderings, while macroscopic spontaneous polarization is always absent. Herein, we report the direct observation of robust out-of-plane ferroelectricity in 2D vdW CuCrP2S6 at room temperature with a comprehensive investigation. Modification of the ferroelectric polarization states in 2D CuCrP2S6 nanoflakes is experimentally demonstrated. Moreover, external electric field-induced polarization switching and hysteresis loops are obtained in CuCrP2S6 down to ~2.6 nm (4 layers). By using atomically resolved scanning transmission electron microscopy, we unveil the origin of the emerged room-temperature ferroelectricity in 2D CuCrP2S6. Our work can facilitate the development of multifunctional nanodevices and provide important insights into the nature of ferroelectric ordering of this 2D vdW material.

Correction: Hybrid lanthanide nanoparticles as a new class of binary contrast agents for in vivo T1/T2 dual-weighted MRI and synergistic tumor diagnosis.

Correction for 'Hybrid lanthanide nanoparticles as a new class of binary contrast agents for in vivo T1/T2 dual-weighted MRI and synergistic tumor diagnosis' by Zhigao Yi et al., J. Mater. Chem. B, 2016, 4, 2715-2722, https://doi.org/10.1039/C5TB02375K.

A pH/GSH/Glucose Responsive Nanozyme for Tumor Cascade Amplified Starvation and Chemodynamic Theranostics.

Nanozymes have brought enormous opportunities for disease theranostics. Here, a self-enhanced catalytic nanocrystal based on a bismuth-manganese core-shell nanoflower containing glucose oxide (GOx), termed BDS-GOx@MnOx, was designed for 4T1 tumor theranostics in vitro and in vivo. The BDS-GOx@MnOx nanozymes enable enhanced starvation treatment (ST) and chemotherapy (CDT) with high efficacy and exhibit sensitive tumor microenvironment (TME) responsive character for tumor therapy as well as for tumor-enhanced computer tomography (CT) and magnetic resonance (MR) diagnostic imaging. The characters and mechanism of the BDS-GOx@MnOx nanozymes have also been systematically studied and revealed.

Polysaccharides from Paecilomyces hepiali Prevent Acute Colitis in Association with Modulating Gut Microbiota and Treg/Th17 Immune Balance in Mice.

Cordyceps exopolysaccharide (CEP) has shown emerging potential in adjustment of gut microbiota and immune cell function. In this study, a water-soluble CEP with a molecular weight of 58.14 kDa was extracted from the fermentation broth of Paecilomyces hepiali, an endophytic fungus of Cordyceps sinensis. Our results indicated that Paecilomyces hepiali polysaccharide (PHP) showed significantly preventive potential on dextran sulfate sodium (DSS)-induced colitis in mice, which can prevent colon shortening, reduce intestinal epithelial cell (IEC) destruction, suppress inflammatory cell infiltration, and regulate the balance between regulatory T (Treg) cells and T helper type 17 (Th17) cells. Meanwhile, the disturbed gut microbiota was partially restored after PHP treatment. Further Pearson correlation coefficient analyses exhibited that the alteration of the gut microbiota was significantly related to adjustment of the IEC barrier and Treg/Th17 balance. In conclusion, all findings proposed that purified PHP has the potential to develop into a promising agent for colitis prevention and adjuvant therapy via maintaining intestinal homeostasis of gut microbiota and immune system.

Achieving reinforcement learning in a three-active-terminal neuromorphic device based on a 2D vdW ferroelectric material.

Currently, for most three-terminal neuromorphic devices, only the gate terminal is active. The inadequate modes and freedom of modulation in such devices greatly hinder the implementation of complex neural behaviors and brain-like thinking strategies in hardware systems. Taking advantage of the unique feature of co-existing in-plane (IP) and out-of-plane (OOP) ferroelectricity in two-dimensional (2D) ferroelectric α-In2Se3, we construct a three-active-terminal neuromorphic device where any terminal can modulate the conductance state. Based on the co-operation mode, controlling food intake as a complex nervous system-level behavior is achieved to carry out positive and negative feedback. Specifically, reinforcement learning as a brain-like thinking strategy is implemented due to the coupling between polarizations in different directions. Compared to the single modulation mode, the chance of the agent successfully obtaining the reward in the Markov decision process is increased from 68% to 82% under the co-operation mode through the coupling effect between IP and OOP ferroelectricity in 2D α-In2Se3 layers. Our work demonstrates the practicability of three-active-terminal neuromorphic devices in handling complex tasks and advances a significant step towards implementing brain-like learning strategies based on neuromorphic devices for dealing with real-world challenges.

Black Phosphorus/Ferroelectric P(VDF-TrFE) Field-Effect Transistors with High Mobility for Energy-Efficient Artificial Synapse in High-Accuracy Neuromorphic Computing.

The neuromorphic system is an attractive platform for next-generation computing with low power and fast speed to emulate knowledge-based learning. Here, we design ferroelectric-tuned synaptic transistors by integrating 2D black phosphorus (BP) with a flexible ferroelectric copolymer poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)). Through nonvolatile ferroelectric polarization, the P(VDF-TrFE)/BP synaptic transistors show a high mobility value of 900 cm2 V-1 s-1 with a 103 on/off current ratio and can operate with low energy consumption down to the femtojoule level (∼40 fJ). Reliable and programmable synaptic behaviors have been demonstrated, including paired-pulse facilitation, long-term depression, and potentiation. The biological memory consolidation process is emulated through ferroelectric gate-sensitive neuromorphic behaviors. Inspiringly, the artificial neural network is simulated for handwritten digit recognition, achieving a high recognition accuracy of 93.6%. These findings highlight the prospects of 2D ferroelectric field-effect transistors as ideal building blocks for high-performance neuromorphic networks.

Memristors based on 2D MoSe2 nanosheets as artificial synapses and nociceptors for neuromorphic computing.

Neuromorphic computing inspired by the human brain is highly desirable in the artificial intelligence age. Thus, it is essential to comprehensively investigate the neuromorphic characteristics of artificial synapses and neurons which are the unit cells in an artificial neural network (ANN). Memristors are considered ideal candidates to serve as artificial synapses and neurons in the ANN. Herein, two-terminal memristors based on two-dimensional (2D) MoSe2 nanosheets are fabricated, demonstrating analog resistive switching (RS) behaviors. Unlike the digital RS behaviors with a sharp transition between the two resistance states, the analog RS provides a series of tunable resistance states, which is more suitable for the realization of synaptic plasticity. Thus, the fabricated memristors successfully implement the synaptic functions, such as paired-pulse facilitation, long-term potentiation and long-term depression. The analog memristors can be utilized to construct the ANN for image recognition, leading to a high recognition accuracy of 92%. In addition, the synaptic memristors can emulate the "learning-forgetting" experience of the human brain. Furthermore, to demonstrate the ability of single neuron learning in our devices, the memristors are studied as artificial nociceptors to recognize noxious stimuli. Our research provides comprehensive investigations on the neuromorphic characteristics of artificial synapses and nociceptors, suggesting promising prospects for applications in neuromorphic computing based on 2D MoSe2 nanosheets.