Photonic implementation of the input and reservoir layers for a reservoir computing system based on a single VCSEL with two Mach-Zehnder modulators.

Hardware implementation of reservoir computing (RC), which could reduce the power consumption of machine learning and significantly enhance data processing speed, holds the potential to develop the next generation of machine learning hardware devices and chips. Due to the existing solution only implementing reservoir layers, the information processing speed of photonics RC system are limited. In this paper, a photonic implementation of a VMM-RC system based on single Vertical Cavity Surface Emitting Laser (VCSEL) with two Mach Zehnder modulators (MZMs) has been proposed. Unlike previous work, both the input and reservoir layers are realized in the optical domain. Additionally, the impact of various mask signals, such as Two-level mask, Six-level mask, and chaos mask signal, employed in system, has been investigated. The system's performance improves with the use of more complex mask(t). The minimum Normalized mean square error (NMSE) can reach 0.0020 (0.0456) for Santa-Fe chaotic time series prediction in simulation (experiment), while the minimum Word Error Rate (WER) can 0.0677 for handwritten digits recognition numerically. The VMM-RC proposed is instrumental in advancing the development of photonic RC by overcoming the long-standing limitations of photonic RC systems in reservoir implementation. Linear matrix computing units (the input layer) and nonlinear computing units (the reservoir layer) are simultaneously implemented in the optical domain, significantly enhancing the information processing speed of photonic RC systems.

Nebulized inhalation of plasma-activated water in the treatment of progressive moderate COVID-19 patients with antiviral treatment failure: a randomized controlled pilot trial.

BACKGROUND: Antiviral drugs show significant efficacy in non-severe COVID-19 cases, yet there remains a subset of moderate COVID-19 patients whose pneumonia continues to progress post a complete course of treatment. Plasma-activated water (PAW) possesses anti-SARS-CoV-2 properties. To explore the potential of PAW in improving pneumonia in COVID-19 patients following antiviral treatment failure, we conducted this study. METHODS: This was a randomized, controlled trial. Moderate COVID-19 patients with antiviral treatment failure were randomly assigned to the experimental group or the control group. They inhaled nebulized PAW or saline respectively. This was done twice daily for four consecutive days. We assessed improvement in chest CT on day 5, the rate of symptom resolution within 10 days, and safety. RESULTS: A total of 23 participants were included, with 11 receiving PAW and 12 receiving saline. The baseline characteristics of both groups were comparable. The experimental group showed a higher improvement rate in chest CT on day 5 (81.8% vs. 33.3%, p = 0.036). The cumulative disappearance rate of cough within 10 days was higher in the experimental group. Within 28 days, 4 patients in each group progressed to severe illness, and no patients died. No adverse reactions were reported from inhaling nebulized PAW. CONCLUSION: This pilot trial preliminarily confirmed that nebulized inhalation of PAW can alleviate pneumonia in moderate COVID-19 patients with antiviral treatment failure, with no adverse reactions observed. This still needs to be verified by large-scale studies. TRIAL REGISTRATION: Chinese Clinical Trial Registry; No.: ChiCTR2300078706 (retrospectively registered, 12/15/2023); URL: www.chictr.org.cn .

CLCA1 exacerbates lung inflammation via p38 MAPK pathway in acute respiratory distress syndrome.

Recent research has revealed that airway epithelial calcium-activated chloride channel-1 (CLCA1) is implicated in the inflammation of multiple human respiratory diseases, but the specific role in acute respiratory distress syndrome (ARDS) remains unknown. To investigate the role of CLCA1 in ARDS, 80 participants, including 26 ARDS patients, 26 patients with community-acquired pneumonia (CAP) and 28 control subjects, were enrolled in this study. As the result shows, the level of CLCA1 was significantly increased in ARDS patients and positively correlated with neutrophil infiltration and the poor prognosis of ARDS. Then, the level of CLCA1 also elevated in the LPS-induced ARDS mouse model, and the administration of CLCA1 significantly regulated the phenotypes of ARDS in mice, such as lung injury score, BALF protein concentration, neutrophils infiltration and the secretions of inflammatory factors. Furthermore, administration of CLCA1 substantially altered the phosphorylation of p38 in the ARDS mouse model, whereas repressing the expression of CLCA1 or inhibiting the activation of p38 both alleviated the inflammatory response of ARDS. In summary, CLCA1 was notably correlated with ARDS and exacerbated the ARDS phenotypes through the p38 MAPK pathway.

Hybrid photonic deep convolutional residual spiking neural networks for text classification.

Spiking neural networks (SNNs) offer powerful computation capability due to its event-driven nature and temporal processing. However, it is still limited to shallow structure and simple tasks due to the training difficulty. In this work, we propose a deep convolutional residual spiking neural network (DCRSNN) for text classification tasks. In the DCRSNN, the feature extraction is achieved via a convolution SNN with residual connection, using the surrogate gradient direct training technique. Classification is performed by a fully-connected network. We also suggest a hybrid photonic DCRSNN, in which photonic SNNs are used for classification with a converted training method. The accuracy of hard and soft reset methods, as well as three different surrogate functions, were evaluated and compared across four different datasets. Results indicated a maximum accuracy of 76.36% for MR, 91.03% for AG News, 88.06% for IMDB and 93.99% for Yelp review polarity. Soft reset methods used in the deep convolutional SNN yielded slightly better accuracy than their hard reset counterparts. We also considered the effects of different pooling methods and observation time windows and found that the convergence accuracy achieved by convolutional SNNs was comparable to that of convolutional neural networks under the same conditions. Moreover, the hybrid photonic DCRSNN also shows comparable testing accuracy. This work provides new insights into extending the SNN applications in the field of text classification and natural language processing, which is interesting for the resources-restrained scenarios.

Noisy image segmentation based on synchronous dynamics of coupled photonic spiking neurons.

The collective dynamics in neural networks is essential for information processing and has attracted much interest on the application in artificial intelligence. Synchronization is one of the most dominant phenomenon in the collective dynamics of neural network. Here, we propose to use the spiking dynamics and collective synchronization of coupled photonic spiking neurons for noisy image segmentation. Based on the synchronization mechanism and synchronization control, the noised pattern segmentation is demonstrated numerically. This work provides insight into the possible application based on the collective dynamics of large-scale photonic networks and opens a way for ultra-high speed image processing.

BP-based supervised learning algorithm for multilayer photonic spiking neural network and hardware implementation.

We introduce a supervised learning algorithm for photonic spiking neural network (SNN) based on back propagation. For the supervised learning algorithm, the information is encoded into spike trains with different strength, and the SNN is trained according to different patterns composed of different spike numbers of the output neurons. Furthermore, the classification task is performed numerically and experimentally based on the supervised learning algorithm in the SNN. The SNN is composed of photonic spiking neuron based on vertical-cavity surface-emitting laser which is functionally similar to leaky-integrate and fire neuron. The results prove the demonstration of the algorithm implementation on hardware. To seek ultra-low power consumption and ultra-low delay, it is great significance to design and implement a hardware-friendly learning algorithm of photonic neural networks and realize hardware-algorithm collaborative computing.

Effects of administration of α2 adrenergic receptor agonist into psoas major muscle on inflammatory pain induced by injection of complete Freund's adjuvant in rats.

α2 adrenergic agonists are widely used in clinical anesthesia and ICU sedation owing to their effective sedative and analgesic effects. Lumbago and leg pain is the most common clinical pain disease. Studies have reported that lumbago and leg pain is associated with dysregulation of paravertebral muscles, especially psoas major muscles. In the present study, a unilateral lower extremity chronic inflammation and pain model was established by subcutaneous administration of low-dose complete Fredrin's adjuvant (CFA) into the posterior paw of rats. α2 adrenalin receptor agonist was then injected into the psoas major muscle. Behavioral tests were conducted for 21 days. Psoas major muscle tissue was harvested for evaluation of biochemical indexes related to pain. The effect of α2 adrenergic receptor agonist injected into psoas major muscle on chronic inflammatory pain of lower extremities in rats was explored. The results showed that injection of α2 adrenergic receptor agonist into the psoas major muscle relieved CFA-induced mechanical hyperalgesia. Administration of α2 adrenergic receptor antagonist yohimbine reversed the analgesic effect of α2 adrenergic receptor agonists. Administration of dexmedetomidine into psoas major muscle downregulated the levels of norepinephrine, interleukin-6 and tumor necrosis factor-α in tissues. The findings of the present study show that administration of α2 adrenoceptor agonists into the psoas major muscle relieves chronic inflammatory pain induced by CFA. Local injection of dexmedetomidine also exerted anti-inflammatory and anti-sympathetic effect by activating α2-adrenoceptor in the psoas major muscle.

Time-delay signature concealment of chaos and ultrafast decision making in mutually coupled semiconductor lasers with a phase-modulated Sagnac loop.

We propose and experimentally demonstrate the generation of dual-channels chaos with time delay signature (TDS) concealment by introducing a phase-modulated Sagnac loop in mutually coupled semiconductor lasers (MCSL). Furthermore, we demonstrate the utilization of the dual-channels chaos to solve multi-armed bandit (MAB) problem in reinforcement learning. The experimental results agree well with the numerical simulations. For the purpose of comparison, the MCSL with a conventional Sagnac loop is also considered. It is found that the TDS of dual-channels chaotic signals can be better concealed in our proposed system. Besides, the proposed system allows for a better decision making performance in MAB problem. Moreover, compared with the one-channel chaotic system, the proposed dual-channels chaotic system achieves ultrafast decision making in parallel, and thus, is highly valuable for further improving the security of communication systems and the performance of photonic intelligence.

Complexity-enhanced polarization-resolved chaos in a ring network of mutually coupled vertical-cavity surface-emitting lasers with multiple delays.

The complexity properties of polarization-resolved chaotic signals generated in a ring network of vertical-cavity surface-emitting lasers (VCSELs) mutually coupled with multiple delays are investigated quantitatively by using the proposed mean permutation entropy (MPE). For direct comparison, the complexity of polarization-resolved chaos in a ring network of VCSELs coupled with single delay is also considered. The effects of injection current, coupling strength, and frequency detuning on the chaotic complexity for both a single-delay ring network (SDRN) and a multiple-delay ring network (MDRN) are evaluated quantitatively and compared by the MPE. The effects of internal parameters of VCSELs on the complexity are also discussed, and the correlation properties between different polarization-resolved modes are also analyzed. It is shown that the complexity of chaos in two polarization-resolved modes of VCSELs in MDRN is much higher than those in SDRN in a much wider parameter region. Besides, wider range of injection current, coupling strength, and frequency detuning can be tuned to achieve the enhancement of chaotic complexity in MDRN. These results provide an effective quantifier, the proposed MPE, to evaluate quantitatively the complexity of chaos generated in systems with multiple delays, and the multichannel complexity-enhanced polarization-resolved chaos generated in MDRN of mutually coupled VCSELs is extremely meaningful for the chaos-based random number generators.

Resistive spontaneous breathing exacerbated lipopolysaccharide-induced lung injury in mice.

Background: Spontaneous respiratory mechanical force interacted with the primary lung injury and aggravated the progression of ARDS clinically. But the exact role and involved mechanism of it in the pathogenesis of ARDS animal model remained obscure. Aim: This study was to investigate the effect of spontaneous respiratory mechanical force on lung injury of ARDS in mice. Methods: Female C57BL/6 mice were subjected to resistive spontaneous breathing (RSB) by tracheal banding after 4-6 h of intranasal inhalation of LPS. Pulmonary function was examined by Buxco system, partial pressures of oxygen and carbon dioxide (PO2 and PCO2) were measured by a blood gas analyzer, and lung pathological changes were analyzed with hematoxylin and eosin staining. The levels of inflammatory markers were quantified by ELISA, total protein assay, and FACS analysis. The expression levels of mechanosensitive ion channels were detected by qRT-PCR and immunohistochemistry. Results: The airway resistance (Raw) was increased and the tidal volume (TV) was decreased remarkedly in RSB group. RSB treatment did not affect PO2, PCO2, pathology and inflammation levels of lung in mice. The Raw increased and ventilatory indicators decreased in RSB + ARDS compared to ARDS significantly. Besides, RSB treatment deteriorated the changes of PO2, PCO2 and level of lactic acid induced by LPS. Meanwhile, RSB significantly promoted LPS-induced pulmonary histopathological injury, and elevated the levels of IL-1ß, IL-6, TNF-α and total proteins, increased neutrophils infiltration. The expression level of Piezo1 in RSB + ARDS group was remarkably reduced compared to ARDS group and consistent with the severity of pulmonary damage. Conclusion: RSB exacerbated LPS-induced ARDS hypoxemia and hypercapnia, inflammation and damage. The mechanosensitive protein Piezo1 expression decreased and may play an important role in the process.

Patient self-inflicted lung injury associated pneumothorax/pneumomediastinum is a risk factor for worse outcomes of severe COVID-19: a case-control study.

We aimed to determine the clinical characteristics of patient self-inflicted lung injury (P-SILI)-associated pneumothorax/pneumomediastinum, to reveal its risk factors, and to assess its impact on severe COVID-19 cases. In total, 229 patients were included in this case-control study. They were randomly divided into either the case group or the control group as per the inclusion and exclusion criteria. The two groups were further analyzed to reveal the risk factors of spontaneous pneumothorax/pneumomediastinum (SP/P). Finally, risk factors for death were analyzed in the case group and the relationship between death and SP/P was also analyzed among all patients. The mean age of patients was 59.69 ± 17.01 years, most of them were male (74.2%), and 62.0% of them had comorbidities upon admission. A respiratory rate higher than 30 BPM was a risk factor for SP/P (OR 7.186, 95% CI 2.414-21.391, P < 0.001). Patients with delayed intubation due to early application of HFNC or NIV had a higher mortality rate when they developed SP/P (P < 0.05). Additionally, advanced age increased the risk of death (P < 0.05). Finally, SP/P may be a risk factor for death among patients with severe COVID-19 (OR 2.047). P-SILI occurs in severe COVID-19 with acute respiratory failure. It is necessary to identify the risk factors of P-SILI, the indicators of severe P-SILI, and the preventive measures.

Rust Prevention Property of a New Organic Inhibitor under Different Conditions.

The corrosion resistance properties of a new type of environmentally-friendly organic inhibitor containing amino ketone molecules are presented in this paper. To evaluate the prevention effect of the inhibitor on corrosion of reinforcement, the electrochemical characteristics of steels in the simulated concrete pore solution (SPS) were investigated under varied conditions of the relevant parameters, including concentrations of the inhibitor and NaCl, pH value, and temperature. The inhibition efficiency of the material was characterized through electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, and the weight loss of steels. The results reveal a significant improvement in the corrosion resistance of steels with the inhibitor. A maximum resistance value of 89.07% was achieved at an inhibitor concentration of 4%. Moreover, the new organic inhibitor exhibited good corrosion protection capability for steels under different NaCl concentrations. Its inhibition efficiency was determined to be 65.62, 80.06, and 66.30% at NaCl concentrations of 2, 3.5 and 5%, respectively. On the other hand, it was found that an alkaline environment was favorable for an enhanced corrosion prevention effect, and an optimal pH value of 11.3 was observed in this work. Besides, the inhibition efficiencies at different temperatures showed a trend of 25 > 35 > 40 > 20 > 30 °C, with a maximum value of 81.32% at 25 °C. The above results suggest that the new organic material has high potential to be used as an eco-friendly and long-term durable inhibitor for steel corrosion prevention under complex conditions.

A configurational analysis on career success of scientific and technological innovation talents in universities.

Introduction: Increasing the career success of scientific and technological innovation talents has become an important means of keeping and using talents in countries around the world. However, the problem has not been solved effectively. Methods: Thirty-five cases were chosen in this study. The combined effects of human capital, psychological capital, micro-social capital, team social capital, and macro-social capital on the career success of scientific and technological innovation talents, as well as relevant influencing mechanisms, were discussed using qualitative comparative analysis (QCA). Results: Results demonstrate that: (a) while a single factor cannot be the only condition for the high career success of scientific and technological innovation talents in universities, increasing macro-social capital plays a relatively universal role in a high career success rate. (b) There are three paths driving the high career success of scientific and technological innovation talents in universities. (c) There are two paths driving the non-high career success of scientific and technological innovation. Both have characteristics of absent psychological capital and micro-social capital. Moreover, the driving mechanism of high career success has an asymmetrical causal relationship. Discussion: Research conclusions are not only conducive to expanding the research perspectives of social capital theory and career success, but also provide valuable insight into how to stimulate the career success of scientific and technological innovation talents in universities.

The Effect of Health Shock and Basic Medical Insurance on Family Educational Investment for Children in China.

This paper explores the role of basic medical insurance in protecting family investment in child education. First, this paper establishes a two-phase overlapping generation model to theoretically analyse the impact of basic medical insurance on investment in child education under the influence of the impact of parental health. The results show that health shock reduces parental investment in child education, and medical insurance significantly alleviates the negative impact of parental health shock on investment in child education. Furthermore, this paper establishes a two-way fixed effect regression model based on the data of China Family Panel Studies (CFPS) in 2014 and 2016 to empirically test the above results. The results showed that parental health shocks negatively affect investment in child education, and paternal health shock has a more significant impact than maternal health shock. However, medical insurance significantly reduces this negative impact, provides security in investment in child education, and promotes the improvement of human capital.

Computing Primitive of Fully VCSEL-Based All-Optical Spiking Neural Network for Supervised Learning and Pattern Classification.

We propose computing primitive for an all-optical spiking neural network (SNN) based on vertical-cavity surface-emitting lasers (VCSELs) for supervised learning by using biologically plausible mechanisms. The spike-timing-dependent plasticity (STDP) model was established based on the dynamics of the vertical-cavity semiconductor optical amplifier (VCSOA) subject to dual-optical pulse injection. The neuron-synapse self-consistent unified model of the all-optical SNN was developed, which enables reproducing the essential neuron-like dynamics and STDP function. Optical character numbers are trained and tested by the proposed fully VCSEL-based all-optical SNN. Simulation results show that the proposed all-optical SNN is capable of recognizing ten numbers by a supervised learning algorithm, in which the input and output patterns as well as the teacher signals of the all-optical SNN are represented by spatiotemporal fashions. Moreover, the lateral inhibition is not required in our proposed architecture, which is friendly to the hardware implementation. The system-level unified model enables architecture-algorithm codesigns and optimization of all-optical SNN. To the best of our knowledge, the computing primitive of an all-optical SNN based on VCSELs for supervised learning has not yet been reported, which paves the way toward fully VCSEL-based large-scale photonic neuromorphic systems with low power consumption.

Efficient xylan-to-sugar biotransformation using an engineered xylanase in hyperthermic environment.

Hyperthermophilic xylanases play a critical role in bioconversion from xylan to sugar in the process of biomass utilization. The discovery of new or improvement of existing xylanases based on directed evolution is expected to be an effective approach to meet the increasing demand of thermostable xylanases. In this work, a xylanase B gene (CTN_0623) from Thermotoga neapolitana (Tne) was cloned and xylanase B (herein named TnexlnB) was solubly expressed in E. coli with a high amount using a heat shock vector pHsh. TnexlnB showed the highest endo-ß-1,4-xylan hydrolase activity at 75 °C and pH 6.0. Additionally, 1 mM Mg2+, Ba2+ and Ca2+ improved the activity of TnexlnB by 31%, 37%, and 53%, respectively. The optimal temperature reached 85 °C by site-directed mutation at the last three helices of TnexlnB. Km and Vmax towards birchwood xylan were determined for both wide type and the best mutant, as follow: 1.09 mg/mL, 191.76 U/mg and 0.29 mg/mL, 376.42 U/mg, respectively. Further characterization highlighted good thermal stability (>80% of enzymatic activity after 1 h at 90 °C) for the best mutant, which made this enzyme suitable for biomass degradation at high temperature.

Erosion characteristics of different reclaimed substrates on iron tailings slopes under simulated rainfall.

Water-induced erosion of iron tailings is a serious problem affecting ecological restoration, but, little is known about how the occurrence of erosion on tailings slopes and types of reclaimed substrates that are beneficial to reducing slope erosion. This study measured the slope erosion characteristics of six reclaimed substrates including loose tailings (LT), crusty tailings (CT), tailings incorporating mushroom residues (TM), tailings incorporating soil (TS), tailings incorporating soil and mushroom residues (TSM) and soil (S) in experimental soil flumes under three simulated intermittent rainfall events, with intensity of 60, 90 and 120 mm h-1 for the first, second and third event, respectively. Significant differences (p < 0.05) were found in erosion characteristics among the six reclaimed substrates. TM had the lowest sediment yield but the highest runoff volume without obvious rills. LT, CT and TS had the highest sediment yield rates and severe slope erosion morphology. With the increased number of rainfall events, the runoff rates of the six substrates all increased, but only the sediment yield rates of LT, CT and TS increased, the sediment yield rates of other substrates increased first and then decreased. Therefore, adding agricultural organic wastes such as mushroom residues to tailings and reducing soil addition may be an effective way to reduce erosion and promote ecological restoration in soilless tailings areas.

Photochemical transformation of perfluoroalkyl acid precursors in water using engineered nanomaterials.

The production of perfluoroalkyl acids (PFAAs) has been phased out over recent decades; however, no significant decline in their environmental concentrations has been observed. This is partly due to the photochemical decomposition of PFAAs precursors (PrePFAAs) which remain in extensive use. The decomposition of PrePFAAs may be accelerated by the light-activated engineered nanomaterials (ENMs) in water. In light of this hypothesis, we investigated the photochemical transformation of three PrePFAAs, which are 8:2 fluorotelomer sulfonic acid (8:2 FTSA), 8:2 fluorotelomer alcohol (8:2 FTOH), and 2-(N-ethylperfluorooctane-1-sulfonamido ethyl] phosphate (SAmPAP), in the presence of six ENMs under simulated sunlight irradiation. The transformation rates of 8:2 FTSA and 8:2 FTOH were increased by 2-6 times when in the presence of six ENMs. However, most of ENMs appeared to inhibit the decomposition of SAmPAP. The transformation rates of PrePFAAs were found to depend on the yield of reactive oxygen species generated by ENMs, but the rates were also related to compound photo-stability, adsorption to surfaces, and photo-shielding effects. The PrePFAAs are transformed to perfluorooctanoic acid (PFOA) or/and perfluorooctane sulfonate (PFOS) with higher toxicity and longer half-life, PFOA or PFOS and a few PFAAs having shorter carbon chain lengths. Higher concentrations of the PFAAs photodegradation products were observed in the presence of most of the ENMs.

Polarization-resolved and polarization- multiplexed spike encoding properties in photonic neuron based on VCSEL-SA.

The spike encoding properties of two polarization-resolved modes in vertical-cavity surface-emitting laser with an embedded saturable absorber (VCSEL-SA) are investigated numerically, based on the spin-flip model combined with the Yamada model. The results show that the external input optical pulse (EIOP) can be encoded into spikes in X-polarization (XP) mode, Y-polarization (YP) mode, or both XP and YP modes. Furthermore, the numerical bifurcation diagrams show that a lower (higher) strength of EIOP is beneficial for generating tonic (phasic) spikes; a small amplitude anisotropy contributes to wide (narrow) tonic spiking range in XP (YP) mode; a large current leads to low thresholds of EIOP strength for both XP and YP modes. However, the spike encoding properties are hardly affected by the phase anisotropy. The encoding rate is shown to be improved by increasing EIOP strength. Moreover, dual-channel polarization-multiplexed spike encoding can also be achieved in a single VCSEL-SA. To the best of our knowledge, such single channel polarization-resolved and dual-channel polarization-multiplexed spike encoding schemes have not yet been reported. Hence, this work is valuable for ultrafast photonic neuromorphic systems and brain-inspired information processing.

Biocompatible zwitterionic phosphorylcholine polymers with aggregation-induced emission feature.

Two novel zwitterionic phosphorylcholine polymers (MTP1 and MTP2) with aggregation-induced emission (AIE) feature were prepared through reversible addition fragmentation chain transfer polymerization between an AIE monomer with vinyl end group and a zwitterionic phosphorylcholine monomer. The synthesized copolymers were characterized and confirmed by 1H NMR, FT-IR, and X-ray photoelectron spectra. By introduction of the zwitterionic phosphorylcholine component, the synthesized copolymers showed amphiphilic properties and tended to self-assemble into fluorescent polymeric nanoparticles (FPNs) in water. The dynamic light scattering results indicated the size distribution of the MTP1 FPNs was 345±22nm, and that of the MTP2 FPNs was 147±36nm. The transmission electron microscopy results demonstrated spherical nanoparticle morphology for the FPNs. The high dispersibility of the FPNs in water was proved by the UV-vis absorption study with high transmittance of the solution. Fluorescent spectra of the prepared FPNs revealed bright green fluorescence with high fluorescence quantum yield of 45% for MTP1 and 34% for MTP2. More importantly, the FPNs showed excellent particle stability with low critical micelle concentration of 0.008mgmL-1 for MTP1 and 0.007mgmL-1 for MTP2. The cytotoxicity evaluation confirmed high cytocompatibility of the prepared FPNs at different concentrations, and demonstrated excellent biocompatibility for cell imaging. In virtue of the high-performance MTP1 and MTP2 FPNs, including high water dispersion, good particle stability, and excellent cytocompatibility, this work would inspire more researches about high-performance biocompatible fluorescent polymers for biomedical application.