Elucidating the catalytic mechanism of Prussian blue nanozymes with self-increasing catalytic activity.

Although Prussian blue nanozymes (PBNZ) are widely applied in various fields, their catalytic mechanisms remain elusive. Here, we investigate the long-term catalytic performance of PBNZ as peroxidase (POD) and catalase (CAT) mimetics to elucidate their lifespan and underlying mechanisms. Unlike our previously reported Fe3O4 nanozymes, which exhibit depletable POD-like activity, the POD and CAT-like activities of PBNZ not only persist but slightly enhance over prolonged catalysis. We demonstrate that the irreversible oxidation of PBNZ significantly promotes catalysis, leading to self-increasing catalytic activities. The catalytic process of the pre-oxidized PBNZ can be initiated through either the conduction band pathway or the valence band pathway. In summary, we reveal that PBNZ follows a dual-path electron transfer mechanism during the POD and CAT-like catalysis, offering the advantage of a long service life.

Breaking the pH Limitation of Nanozymes: Mechanisms, Methods, and Applications.

Although nanozymes have drawn great attention over the past decade, the activities of peroxidase-like, oxidase-like, and catalase-like nanozymes are often pH dependent with elusive mechanism, which largely restricts their application. Therefore, a systematical discussion on the pH-related catalytic mechanisms of nanozymes together with the methods to overcome this limitation is in need. In this review, various nanozymes exhibiting pH-dependent catalytic activities are collected and the root causes for their pH dependence are comprehensively analyzed. Subsequently, regulatory concepts including catalytic environment reconstruction and direct catalytic activity improvement to break this pH restriction are summarized. Moreover, applications of pH-independent nanozymes in sensing, disease therapy, and pollutant degradation are overviewed. Finally, current challenges and future opportunities on the development of pH-independent nanozymes are suggested. It is anticipated that this review will promote the further design of pH-independent nanozymes and broaden their application range with higher efficiency.

Platelet rich plasma combined with arthroscopic microfracture versus arthroscopic microfracture alone for the treatment of knee cartilage injury.

OBJECTIVE: To investigate the clinical efficacy of platelet-rich plasma (PRP) injection combined with arthroscopic microfracture technique in treating knee cartilage injury. METHODS: The clinical data of 120 patients with knee cartilage injuries treated in Jiangnan University Medical Center from October 2019 to December 2021 were analyzed retrospectively. Among them, 55 cases underwent the arthroscopic microfracture technique alone (control group), and the other 65 cases underwent PRP combined with the arthroscopic microfracture technique (observation group). The visual analogue scale (VAS) score, Lysholm knee joint score, MRI image indexes, the incidence of adverse events, and patient satisfaction during treatment were compared between groups before and after surgery. RESULTS: Before surgery and at 3, 6, and 12 months after surgery, VAS scores in both groups showed a decreasing trend with time (F = 40.780, P<0.001); VAS scores in the observation group were lower than those in the control group (F = 302.300, P<0.001); there was an interaction between grouping and time (F = 10.350, P<0.001); Lysholm score in both groups showed an increasing trend with time (F = 153.500, P<0.001); Lysholm scores in the observation group were higher than those in the control group (F = 488.000, P<0.001); there was an interaction between grouping and time (F = 25.570, P<0.001). At 12 months after surgery, the subchondral bone marrow oedema volumes and bone marrow defect areas in the observation group were smaller than those in the control group; while repaired cartilage thicknesses of the observation group were more significant than those of the control group (all P<0.05). Patient satisfaction in the observation group was higher than that the control group (95.38% VS 80%, P<0.05). There was no statistical difference in the incidence of adverse events between the control group and the observation group (7.27% VS 3.64%). The clinical efficacy was judged to be effective in 81 cases and markedly effective in 39 patients. Logistic regression analysis showed that age and body mass index (BMI) were independent factors affecting the treatment efficacy. CONCLUSION: PRP combined with the arthroscopic microfracture technique has high safety in treating knee cartilage injuries. Compared with the arthroscopic microfracture alone, PRP combined with arthroscopic microfracture technique can effectively relieve pain, promote the repair of defective cartilage, improve knee joint function, and increase patient satisfaction. It is worthy of clinical promotion.

Influence factors on illuminance distribution uniformity and energy saving of the indoor illumination control method.

This study investigated the influence factors of illuminance distribution uniformity and the energy-saving ability of the indoor illumination control system, which consists of a white light-emitting diodes (WLED) matrix and a tabletop matrix. In the proposed illumination control method, comprehensive effects of time-invariant and time-variant sunlight of the outdoor environment, arrangement of the WLED matrix, iterative functions selected for illuminance distribution optimization, and compositions of WLED optical spectra are considered. The non-symmetrical spatial distribution of WLED-tabletop matrices, the optical spectrum selection of WLEDs, and the shifting sunlight intensity introduce obvious influence on (a) emission intensity and distribution uniformity of the WLED matrix and (b) receiving illuminance intensity and distribution uniformity of the tabletop matrix. Additionally, the selection of iterative functions, the WLED matrix dimension, the target error coefficient in the iteration, and the optical spectra of the WLEDs cause non-negligible influence on the energy saving percentage and iteration steps of the proposed algorithm, influencing the effectiveness and accuracy of the proposed method. Our investigation provides guidelines for the improvement of optimization speed and accuracy of indoor illumination control systems, and the method is hopefully to be widely applied in manufacturing industry and intelligent office buildings.

A Novel Public Sentiment Analysis Method Based on an Isomerism Learning Model via Multiphase Processing.

The dissemination of public opinion in the social media network is driven by public sentiment, which can be used to promote the effective resolution of social incidents. However, public sentiments for incidents are often affected by environmental factors such as geography, politics, and ideology, which increases the complexity of the sentiment acquisition task. Therefore, a hierarchical mechanism is designed to reduce complexity and utilize processing at multiple phases to improve practicality. Through serial processing between different phases, the task of public sentiment acquisition can be decomposed into two subtasks, which are the classification of report text to locate incidents and sentiment analysis of individuals' reviews. Performance has been improved through improvements to the model structure, such as embedding tables and gating mechanisms. That being said, the traditional centralized structure model is not only easy to form model silos in the process of performing tasks but also faces security risks. In this article, a novel distributed deep learning model called isomerism learning based on blockchain is proposed to address these challenges, the trusted collaboration between models can be realized through parallel training. In addition, for the problem of text heterogeneity, we also designed a method to measure the objectivity of events to dynamically assign the weights of models to improve aggregation efficiency. Extensive experiments demonstrate that the proposed method can effectively improve performance and outperform the state-of-the-art methods significantly.

Reference material of Prussian blue nanozymes for their peroxidase-like activity.

Nanozymes with wide applications have rapidly attracted tremendous attention from various fields in the last decade. However, research on the standardization of nanozymes is still lacking. Currently, the accurate evaluation and effective tracing of the enzyme-like activity of nanozymes have become a common concern. This work aims to develop a certified reference material (CRM) of Prussian blue nanozymes (PBNEs) for their peroxidase (POD)-like activity. The homogeneity and stability studies demonstrated that the property value of POD-like activity is consistent across different packing units, and remains unchanged during the one-year validity period of storage in the dark at 4 °C. The certified value of the POD-like activity of the PBNE CRM is assigned as 174 ± 13 U mg-1 (k = 2) by interlaboratory comparison studies and traceable uncertain evaluation. Furthermore, the need for quality control of the POD-like activity of nanozymes was exemplified by comparing the influence of two additional PBNEs on the dry and wet chemical detection of glucose (Glu). As the first quality assurance tool of nanozymes, the PBNE CRM is expected to replace natural horse radish peroxidase (HRP) as an effective benchmark for assessing the analytical method and laboratory competence. In addition, this work also inspires the further standardization of nanozymes.

Automatic Illumination Control Method for Indoor Luminaires Based on Multichromatic Quantum Dot Light-Emitting Diodes.

Energy saving and visual comfort are two main considerations in designing of automatic illumination control systems. However, energy-saving-oriented illumination control always causes optical spectra drifting in light-conversion-material-based white light-emitting diodes (WLEDs), which are conventionally used as artificial luminaires in indoor areas. In this study, we propose a method for InP quantum dot (QD)-based WLEDs to minimize optical energy consumption by considering the influence caused by the outdoor environment and neighboring WLED units. Factors of (a) dimensions of room window and WLED matrix, (b) distance between WLED units, lighting height, species of InP QDs, and (c) user distribution are taken into consideration in calculation. Parameters of correlated color temperature (CCT) and color rendering index (Ra) of the WLED matrix are optimized according to the lighting environment to improve user visual comfort level. By dynamically controlling the light ingredients and optical power of WLEDs, we optimize the received illuminance distribution of table tops, improve the lighting homogeneity of all users, and guarantee the lowest energy consumption of the WLED matrix. The proposed approach can be flexibly applied in large-scale WLED intelligent controlling systems for industrial workshops and office buildings.

An Investigation on CCT and Ra Optimization for Trichromatic White LEDs Using a Dual-Weight-Coefficient-Based Algorithm.

Spectral optimization is applied as an effective tool in designing solid-state lighting devices. Optimization speed, however, has been seldomly discussed in previous reports as regards designing an algorithm for white light-emitting diodes (WLEDs). In this study, we propose a method for trichromatic WLEDs to obtain the optimal Ra under target correlated color temperatures (CCTs). Blue-, yellow-, and red-color monochromatic spectra, produced by the GaN LED chip, YAG:Ce3+ phosphors, and CdSe/ZnSe quantum dots, respectively, are adopted to synthesize white light. To improve the effectiveness of our method, the concept of dual weight coefficients is proposed, to maintain a numerical gap between the proposed floating CCT and the target CCT. This gap can effectively guarantee that Ra and CCT ultimately move toward the targeting value simultaneously. Mechanisms of interaction between CCT, Ra, and dual-weight coefficients are investigated and discussed in detail. Particularly, a fitting curve is drawn to reveal the linear relationship between weight coefficients and target CCTs. This finding effectively maintains the accuracy and accelerates the optimization process in comparison with other methods with global searching ability. As an example, we only use 29 iterations to achieve the highest Ra of 96.1 under the target CCT of 4000 K. It is hoped that this study facilitates technology development in illumination-related areas such as residential intelligent lighting and smart planting LED systems.

A Novel Method for Food Market Regulation by Emotional Tendencies Predictions from Food Reviews Based on Blockchain and SAEs.

As a part of food safety research, researches on food transactions safety has attracted increasing attention recently. Food choice is an important factor affecting food transactions safety: It can reflect consumer preferences and provide a basis for market regulation. Therefore, this paper proposes a food market regulation method based on blockchain and a deep learning model: Stacked autoencoders (SAEs). Blockchain is used to ensure the fairness of transactions and achieve transparency within the transaction process, thereby reducing the complexity of the trading environment. In order to enhance the usability, relevant Web pages have been developed to make it more friendly and conduct a security analysis for using blockchain. Consumers' reviews after the transactions are finished can be used to train SAEs in order to perform emotional tendencies predictions. Compared with different advanced models for predictions, the test results show that SAEs have a better performance. Furthermore, in order to provide a basis for the formulation of regulation strategies and its related policies, case studies of different traders and commodities have also been conducted, proving the effectiveness of the proposed method.