Physiochemistry and sources of individual particles in response to intensified controls during the 2022 Winter Olympics in Beijing.

To investigate the particle sources before, during, and after the 2022 Beijing Winter Olympic and Paralympic (WOP) in Beijing, ambient particles were passively collected from January to March 2022. The physicochemical properties including morphology, size, shape parameters, and elemental compositions were analyzed by the IntelliSEM EPAS (an advanced computer-controlled scanning electron microscopy [CCSEM] system). Using the user-defined classification rules, 37,174 individual particles were automatically classified into 27 major groups and further attributed to seven major sources based on the source-associated characteristics, including mineral dust, secondary aerosol, combustion/industry, carbonaceous particles, salt-related particles, biological particles, and fiber particles. Our results showed that mineral dust (66.5%), combustion/industry (12.6%), and secondary aerosol (6.3%) were the three major sources in a wide size range of 0.2-42.8 µm. During the Winter Olympic Games period, low emission of anthropogenic particles and favorable meteorological conditions contributed to significantly improved air quality. During the Winter Paralympic Games period, more particles sourced from the dust storm, secondary formed particles, and the adverse meteorological conditions resulted in relatively worse air quality. The secondary aerosol all decreased during the competition period, while increased during the non-competition period. Sulfate-related particles had explosive growth and further aggravate the pollution degree during the non-competition period, especially under adverse meteorological conditions. These results provide microscopic evidence revealing variations of physicochemical properties and sources in response to the control measures and meteorological conditions.

Clinical profile, management and risk factors for seizure-related burn injuries among patients with epilepsy in southwest China.

Objective: The epidemiological information associated with seizure-related burn injuries is lacking in China. Therefore, this study aims to analyze the clinical profile, management, outcome, and risk factors of burns that are directly caused by seizures among epileptic patients, and identify the epidemiological characteristics to develop effective preventive strategies. Methods: This study was conducted between January 2002 and December 2022 in a large Chinese burn center. Data including clinical profile, wound treatment, and outcome were analyzed. A multiple linear regression was used to screen the risk factors for the length of hospital stay (LOS), and a multiple logistic regression was used to screen the contributory factors for the amputation. Results: A total of 184 burn patients (55.98 % females) were enrolled, with a 0.78 % incidence rate during the study period. The mean age of the patients was 36.16 years (SD: 17.93). Patients aged 20-29 were the most affected age groups (23.37 %). Most burns were caused by flame, accounting for 60.33 % (111/184) of all cases. In total, 76.09 % of the 184 patients underwent at least one operation, and 35 patients (19.02 %) still required amputation during the study period. Burn sites (hands) had the greatest impact on amputation (OR = 3.799), followed by flame burns (OR = 3.723). The mean LOS/TBSA was 6.90 ± 8.53 d, and a larger TBSA, full-thickness burns, and a higher number of operations were identified as the risk factors for a longer LOS. There was one death among the 184 patients, with a mortality rate of 0.54 %. Conclusion: This study demonstrates that burn injuries are extremely harmful to individuals with epilepsy in China because they are at high risk of amputation and disability. Effective healthcare education and preventive programs that focus on lifestyle modifications and seizure control should be implemented to reduce the burn incidence in these populations.

Video2Haptics: Converting Video Motion to Dynamic Haptic Feedback with Bio-Inspired Event Processing.

In cinematic VR applications, haptic feedback can significantly enhance the sense of reality and immersion for users. The increasing availability of emerging haptic devices opens up possibilities for future cinematic VR applications that allow users to receive haptic feedback while they are watching videos. However, automatically rendering haptic cues from real-time video content, particularly from video motion, is a technically challenging task. In this paper, we propose a novel framework called "Video2Haptics" that leverages the emerging bio-inspired event camera to capture event signals as a lightweight representation of video motion. We then propose efficient event-based visual processing methods to estimate force or intensity from video motion in the event domain, rather than the pixel domain. To demonstrate the application of Video2Haptics, we convert the estimated force or intensity to dynamic vibrotactile feedback on emerging haptic gloves, synchronized with the corresponding video motion. As a result, Video2Haptics allows users not only to view the video but also to perceive the video motion concurrently. Our experimental results show that the proposed event-based processing methods for force and intensity estimation are one to two orders of magnitude faster than conventional methods. Our user study results confirm that the proposed Video2Haptics framework can considerably enhance the users' video experience.

Evolution of Ozone Formation Sensitivity during a Persistent Regional Ozone Episode in Northeastern China and Its Implication for a Control Strategy.

In recent years, the magnitude and frequency of regional ozone (O3) episodes have increased in China. We combined ground-based measurements, observation-based model (OBM), and the Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model to analyze a typical persistent O3 episode that occurred across 88 cities in northeastern China during June 19-30, 2021. The meteorological conditions, particularly the wind convergence centers, played crucial roles in the evolution of O3 pollution. Daily analysis of the O3 formation sensitivity showed that O3 formation was in the volatile organic compound (VOC)-limited or transitional regime at the onset of the pollution episode in 92% of the cities. Conversely, it tended to be or eventually became a NOx-limited regime as the episode progressed in the most polluted cities. Based on the emission-reduction scenario simulations, mitigation of the regional O3 pollution was found to be most effective through a phased control strategy, namely, reduction of a high ratio of VOCs to NOx at the onset of the pollution and lower ratio during evolution of the O3 episode. This study presents a new possibility for regional O3 pollution abatement in China based on a reasonable combination of OBM and the WRF-CMAQ model.

Effects of norethindrone on the growth, behavior, and thyroid endocrine system of adult female western mosquitofish (Gambusia affinis).

Progestins are mainly used in pharmacotherapy and animal husbandry and have received increasing attention as they are widely detected in various aquatic ecosystems. In this study, adult female western mosquitofish (Gambusia affinis) were exposed to different concentrations of norethindrone (NET) (solvent control, 5.0 (L), 50.0 (M), and 500.0 (H) ng/L) for 42 days. Behaviors, morphological parameters, histology of the thyroid, thyroid hormone levels (TSH, T3, and T4), and transcriptional levels of nine genes in the hypothalamic-pituitary-thyroid (HPT) axis were examined. The results showed that NET decreased sociality but increased the anxiety of G. affinis. Sociality makes fish tend to cluster, and anxiety may cause G. affinis to reduce exploration of new environments. Female fish showed hyperplasia, hypertrophy, and glial depletion in their thyroid follicular epithelial cells after NET treatment. The plasma levels of TSH and T4 were significantly reduced, but T3 concentrations were significantly increased in the fish from the H group. In addition, the transcripts of genes (tshb, tshr, tg, dio1, dio2, thrb) in the brains of fish in the M and H treatments were significantly stimulated, while those of trh and pax2a were suppressed. Our results suggest that NET may impact key social behaviors in G. affinis and interfere with the entire thyroid endocrine system, probably via affecting the transcriptional expression of upstream regulators in the HPT axis.

The multi-media environmental behavior of heavy metals around tailings under the influence of precipitation.

Precipitation can lead to significant leaching of heavy metals from abandoned tailings，resulting in a decline in the quality of the surrounding environment. This study aimed to simulate and quantify the migration patterns and fate of heavy metals in tailings caused by precipitation in various environmental media (tailings, air, water, soil, and sediments) using leaching tests, source apportionment, and a fugacity model. Results revealed that the average contents of Cd, Cu, As, Pb, Zn, and Cr in the un-weathered tailings were 3.43, 495.56, 160.70, 138.94, 536.57, and 69.52 mg/kg, respectively. The ecological risk factors in the tailings as well as in sediments and soils, were in the following order: Cd >Cu >As >Pb >Zn >Cr. A fugacity model based on the mass-balance methods was established, achieving a good agreement between simulation and measured values. The total amounts of Cd, Cu, As, Pb, and Zn leached from abandoned tailings over the 30-year evaluation period were estimated to be 1.09, 62.44, 0.16, 0.94, and 102.12 t, respectively. Soil and sediments are important reservoirs for heavy metals. The sum of the As, Cd, Cu, Pb, and Zn storage capacities in the soil and sediment accounted for 77.28%, 75.63%, 73.94%, 69.39%, and 57.80% of the total storage capacity, respectively. This study could provide the means for the establishment of a targeted pollution control plan, a guide for restoration projects, and will aid in controlling pollution risk and improving the surrounding environment.

Service reliability evaluation of highway tunnel based on digital image processing.

China is gradually transitioning from the "tunnel construction exploration era" to the "tunnel high-quality construction and operation era", and the maintenance demand of highway tunnels has increased sharply. Therefore, there is an urgent need for an evaluation method to evaluate the service reliability of highway tunnels, so as to provide reference for tunnel maintenance personnel to carry out maintenance work. Taking highway tunnels as the research object, this paper extracts three parameters, including length, maximum width and fractal dimension, from the binary image of highway tunnel lining cracks. The standard for dividing the length of the highway tunnel section is 500m as the tunnel section, and a section disease sample space including multiple highway tunnels is constructed. The EM clustering algorithm was used to determine the number of graded grades of disease, and the relative Euclidean distance was used as the evaluation index to divide the safety grade of the tunnel into five grades: normal, degraded, inferior, deteriorated and hazardous. The partial least squares method is used to establish the lining service reliability evaluation formula and verify the residual of each sample point in the sample space. The smaller the average value of the residual, the better fitting effect of the established evaluation formula. The service reliability evaluation method proposed in this paper is applied to engineering practice and compared with the expert scoring method and the national standard method, which proves that the evaluation method in this paper has the advantages of strong visibility, simple evaluation method, and is conducive to engineering practice.

Boosting Efficient and Sustainable Alkaline Water Oxidation on a W-CoOOH-TT Pair-Sites Catalyst Synthesized via Topochemical Transformation.

The development of facile methods for constructing highly active, cost-effective catalysts that meet ampere-level current density and durability requirements for an oxygen evolution reaction is crucial. Herein, a general topochemical transformation strategy is posited: M-Co9 S8 single-atom catalysts (SACs) are directly converted into M-CoOOH-TT (M = W, Mo, Mn, V) pair-sites catalysts under the role of incorporating of atomically dispersed high-valence metals modulators through potential cycling. Furthermore, in situ X-ray absorption fine structure spectroscopy is used to track the dynamic topochemical transformation process at the atomic level. The W-Co9 S8 breaks through the low overpotential of 160 mV at 10 mA cm-2 . A series of pair-site catalysts exhibit a large current density of approaching 1760 mA cm-2 at 1.68 V vs reversible hydrogen electrode (RHE) in alkaline water oxidation and achieve a ≈240-fold enhancement in the normalized intrinsic activity compare to that reported CoOOH, and sustainable stability of 1000 h. Moreover, the O─O bond formation is confirmed via a two-site mechanism, supported by in situ synchrotron radiation infrared and density functional theory (DFT) simulations, which breaks the limit of adsorption-energy scaling relationship on conventional single-site.

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.

Clinical epidemiology and a novel predicting nomogram of central line associated bloodstream infection in burn patients.

Burn patients are at high risk of central line-associated bloodstream infection (CLABSI). However, the diagnosis of such infections is complex, resource-intensive, and often delayed. This study aimed to investigate the epidemiology of CLABSI and develop a prediction model for the infection in burn patients. The study analysed the infection profiles, clinical epidemiology, and central venous catheter (CVC) management of patients in a large burn centre in China from January 2018 to December 2021. In total, 222 burn patients with a cumulative 630 CVCs and 5,431 line-days were included. The CLABSI rate was 23.02 CVCs per 1000 line-days. The three most common bacterial species were Acinetobacter baumannii, Staphylococcus aureus, and Pseudomonas aeruginosa; 76.09% of isolates were multidrug resistant. Compared with a non-CLABSI cohort, CLABSI patients were significantly older, with more severe burns, more CVC insertion times, and longer total line-days, as well as higher mortality. Regression analysis found longer line-days, more catheterisation times, and higher burn wounds index to be independent risk factors for CLABSI. A novel nomogram based on three risk factors was constructed with an area under the receiver operating characteristic curve (AUROC) value of 0.84 (95% CI: 0.782-0.898) with a mean absolute error of calibration curve of 0.023. The nomogram showed excellent predictive ability and clinical applicability, and provided a simple, practical, and quantitative strategy to predict CLABSI in burn patients.

Biomaterials releasing drug responsively to promote wound healing via regulation of pathological microenvironment.

Wound healing is characterized by complex, orchestrated, spatiotemporal dynamic processes. Recent findings demonstrated suitable local microenvironments were necessities for wound healing. Wound microenvironments include various biological, biochemical and physical factors, which are produced and regulated by endogenous biomediators, exogenous drugs, and external environment. Successful drug delivery to wound is complicated, and need to overcome the destroyed blood supply, persistent inflammation and enzymes, spatiotemporal requirements of special supplements, and easy deactivation of drugs. Triggered by various factors from wound microenvironment itself or external elements, stimuli-responsive biomaterials have tremendous advantages of precise drug delivery and release. Here, we discuss recent advances of stimuli-responsive biomaterials to regulate local microenvironments during wound healing, emphasizing on the design and application of different biomaterials which respond to wound biological/biochemical microenvironments (ROS, pH, enzymes, glucose and glutathione), physical microenvironments (mechanical force, temperature, light, ultrasound, magnetic and electric field), and the combination modes. Moreover, several novel promising drug carriers (microbiota, metal-organic frameworks and microneedles) are also discussed.

Efficacy and safety of extracorporeal membrane oxygenation for burn patients: a comprehensive systematic review and meta-analysis.

Background: Respiratory and circulatory dysfunction are common complications and the leading causes of death among burn patients, especially in severe burns and inhalation injury. Recently, extracorporeal membrane oxygenation (ECMO) has been increasingly applied in burn patients. However, current clinical evidence is weak and conflicting. This study aimed to comprehensively evaluate the efficacy and safety of ECMO in burn patients. Methods: A comprehensive search of PubMed, Web of Science and Embase from inception to 18 March 2022 was performed to identify clinical studies on ECMO in burn patients. The main outcome was in-hospital mortality. Secondary outcomes included successful weaning from ECMO and complications associated with ECMO. Meta-analysis, meta-regression and subgroup analyses were conducted to pool the clinical efficacy and identify influencing factors. Results: Fifteen retrospective studies with 318 patients were finally included, without any control groups. The commonest indication for ECMO was severe acute respiratory distress syndrome (42.1%). Veno-venous ECMO was the commonest mode (75.29%). Pooled in-hospital mortality was 49% [95% confidence interval (CI) 41-58%] in the total population, 55% in adults and 35% in pediatrics. Meta-regression and subgroup analysis found that mortality significantly increased with inhalation injury but decreased with ECMO duration. For studies with percentage inhalation injury ≥50%, pooled mortality (55%, 95% CI 40-70%) was higher than in studies with percentage inhalation injury <50% (32%, 95% CI 18-46%). For studies with ECMO duration ≥10 days, pooled mortality (31%, 95% CI 20-43%) was lower than in studies with ECMO duration <10 days (61%, 95% CI 46-76%). In minor and major burns, pooled mortality was lower than in severe burns. Pooled percentage of successful weaning from ECMO was 65% (95% CI 46-84%) and inversely correlated with burn area. The overall rate of ECMO-related complications was 67.46%, and infection (30.77%) and bleedings (23.08%) were the two most common complications. About 49.26% of patients required continuous renal replacement therapy. Conclusions: ECMO seems to be an appropriate rescue therapy for burn patients despite the relatively high mortality and complication rate. Inhalation injury, burn area and ECMO duration are the main factors influencing clinical outcomes.

Emerging Prevalence and Clinical Features of Elizabethkingia meningoseptica Infection in Southwest China: A 9-Year Retrospective Study and Systematic Review.

Background: Elizabethkingia meningoseptica infections have gradually emerged as life-threatening nosocomial infections worldwide, accompanied by increasing incidence, multidrug resistance and poor outcomes. However, the epidemiology and clinical features of E. meningoseptica infection are still limited in mainland China. Methods: Patients with E. meningoseptica infections from 2011 to 2019 in southwestern China were retrospectively analyzed. The clinical features, infection patterns and outcomes were extracted from medical records and analyzed. A comprehensive systematic review was performed in accordance with PRISMA guidelines from conception to August 23, 2021. Results: Ninety-two patients were ultimately included, with the prevalence rapidly rising from 0 in 2011 to 0.19 per 1000 inpatients in 2019. A total of 93.48% of E. meningoseptica isolates were multidrug resistant, including 100% resistance to carbapenem. Furthermore, 75% of E. meningoseptica infections were concomitant with other pathogens. The mortality of our cohort was 36.96%, with risk factors for mechanical ventilation (OR=9.51, P=0.004), male sex (OR=0.27, P=0.031) and more concomitant pathogens. After propensity score matching, central venous catheters, exposure to carbapenem and antifungal drugs, and underlying tumors were associated with E. meningoseptica infection. Sixteen articles were also summarized, with reported mortality rates ranging from 11.0% to 66.6%. Blood and respiratory tract were the common sources. Piperacillin/tazobactam, trimethoprim/sulfamethoxazole, fluoroquinolone and minocycline were the most sensitive antibiotics. Inappropriate antibiotic treatment was the most commonly reported risk factor for mortality. Conclusion: Nosocomial infection with E. meningoseptica has become an emerging problem with high mortality in southwestern China. Inappropriate antibiotic treatment and central venous catheters are risk factors for infection and death and should receive adequate attention.

Evaluating the anthropogenic nitrogen emissions to water using a hybrid approach in a city cluster: Insights into historical evolution, attribution, and mitigation potential.

Anthropogenic reactive nitrogen (Nr) emissions from agricultural production and food consumption in city clusters have caused water quality degradation and scarcity. In this study, anthropogenic Nr emissions to the water environment were quantitatively evaluated in the Yangtze River Delta city cluster from 2011 to 2020 using coupling nitrogen (N) flow analysis and the grey water footprint (GWF) method. The spatiotemporal characteristics of the GWF and the relative contributions of natural and human factors to the water pollution level (WPL) were analyzed. The results showed that from 2011 to 2020, the total N-related GWF decreased by 12.1 %, mainly driven by reduced fertilizer application and livestock numbers. In 2020, the primary pollution source changed from livestock to humans; however, non-point sources still dominated the GWF. The spatial clustering trend of the GWF was significant: high and low GWF were mainly concentrated in the northeast and southwest regions, respectively. From 2011 to 2020, the mean center of the GWF moved west due to the decrease and increase in the eastern and western regions, respectively, supporting the pollution haven hypothesis. The WPL ranged from 2.67 to 5.03 and fluctuated due to variations in precipitation. The relative contributions of natural and human factors to the WPL evolution were 72.9 % and 27.1 %, respectively. According to the scenario analysis, increasing the N use efficiency to 50 %, manure recycling rate to 80 %, and sewage treatment rate in urban and rural regions to 98 % and 40 %, respectively, could decrease GWF by 39.6 %. The present study establishes an open framework to evaluate anthropogenic N emissions to water, and the outcomes provide valuable references for sustainable N management in city clusters.

Extracorporeal Membrane Oxygenation in Acute Respiratory Distress Syndrome Caused by Anhydrous Ammonia Burns: Two Case Reports.

Acute anhydrous ammonia burns are relatively rare but lethal and often occur as a mass occupational incident worldwide. Anhydrous ammonia mainly leads to severe inhalation injury and skin/mucosa wound because of its high water solubility and strong alkalinity. Acute respiratory distress syndrome (ARDS) induced by inhalation injury is the main cause of death. Extracorporeal membrane oxygenation (ECMO), also known as extracorporeal life support, has been recommended as the salvage treatment for severe ARDS based on low-level evidence. However, the application of ECMO in ammonia burns is still limited. Here, we presented two cases of anhydrous ammonia burn patients, one 62-year-old man with 15% total body surface area (TBSA) and one 47-year-old man with 27% TBSA, accompanying severe inhalation injury. They both developed severe ARDS and started vv ECMO on 3, 6, and 15 days after injury, respectively. ECMO lasted 118, 247, and 72 h, respectively. All ECMO were successfully weaned off although only one patient survived. Meanwhile, one patient had the coagulopathy complication of ECMO, mainly bleeding, deep vein thrombosis, and hemolysis. In conclusion, this report provided evidence for use of ECMO as supportive care in ammonia burn patients with severe ARDS.

Construction of rice supply chain supervision model driven by blockchain smart contract.

The outbreak of the COVID-19 and the Russia Ukraine war has had a great impact on the rice supply chain. Compared with other grain supply chains, rice supply chain has more complex structure and data. Using digital means to realize the dynamic supervision of rice supply chain is helpful to ensure the quality and safety of rice. This study aimed to build a dynamic supervision model suited to the circulation characteristics of the rice supply chain and implement contractualization, analysis, and verification. First, based on an analysis of key information in the supervision of the rice supply chain, we built a dynamic supervision model framework based on blockchain and smart contracts. Second, under the logical framework of a regulatory model, we custom designed three types of smart contracts: initialization smart contract, model-verification smart contract, and credit-evaluation smart contract. To implement the model, we combined an asymmetric encryption algorithm, virtual regret minimization algorithm, and multisource heterogeneous fusion algorithm. We then analyzed the feasibility of the algorithm and the model operation process. Finally, based on the dynamic supervision model and smart contract, a prototype system is designed for example verification. The results showed that the dynamic supervision model and prototype system could achieve the real-time management of the rice supply chain in terms of business information, hazard information, and personnel information. It could also achieve dynamic and credible supervision of the rice supply chain's entire life cycle at the information level. This new research is to apply information technology to the digital management of grain supply chain. It can strengthen the digital supervision of the agricultural product industry.

Load Balancing Based on Firefly and Ant Colony Optimization Algorithms for Parallel Computing.

With the wide application of computational fluid dynamics in various fields and the continuous growth of the complexity of the problem and the scale of the computational grid, large-scale parallel computing came into being and became an indispensable means to solve this problem. In the numerical simulation of multi-block grids, the mapping strategy from grid block to processor is an important factor affecting the efficiency of load balancing and communication overhead. The multi-level graph partitioning algorithm is an important algorithm that introduces graph network dynamic programming to solve the load-balancing problem. This paper proposed a firefly-ant compound optimization (FaCO) algorithm for the weighted fusion of two optimization rules of the firefly and ant colony algorithm. For the graph, results after multi-level graph partitioning are transformed into a traveling salesman problem (TSP). This algorithm is used to optimize the load distribution of the solution, and finally, the rough graph segmentation is projected to obtain the most original segmentation optimization results. Although firefly algorithm (FA) and ant colony optimization (ACO), as swarm intelligence algorithms, are widely used to solve TSP problems, for the problems for which swarm intelligence algorithms easily fall into local optimization and low search accuracy, the improvement of the FaCO algorithm adjusts the weight of iterative location selection and updates the location. Experimental results on publicly available datasets such as the Oliver30 dataset and the eil51 dataset demonstrated the effectiveness of the FaCO algorithm. It is also significantly better than the commonly used firefly algorithm and other algorithms in terms of the search results and efficiency and achieves better results in optimizing the load-balancing problem of parallel computing.

A Refined Supervision Model of Rice Supply Chain Based on Multi-Blockchain.

With the development of Agriculture 4.0, the requirements for sustainable agriculture and precision agriculture continue to grow. As one of the three major staple foods globally, the quality and safety of rice affect human health as well as social development. To ensure the quality and safety of rice and reduce the flow of problematic rice, a multi-layer blockchain-based rice supply chain refinement supervision model MBRRSM (Multi-blockchain Rice Refined Supervision Model) is proposed from the information level. First, the characteristics of information flow in the rice supply chain are analyzed, and a classification table of key information is constructed. Second, the MBRRSM framework is designed. Based on a multi-party hybrid encryption algorithm, secure multi-party computing algorithm, multi-mode storage mechanism, and SPOP (Supervision Proof of Peers) consensus algorithm, a set of mechanisms is designed for the transmission, use, storage, and consensus of rice data in MBRRSM. Subsequently, the security and performance capabilities of MBRRSM are analyzed. Meanwhile, the SPOP consensus algorithm is analyzed. Finally, a prototype system is built based on MBRRSM and verified through exemplary scenarios in different usage situations. The results show that research on the refined supervision of the rice supply chain based on multi-blockchain can finely supervise all types of data in the rice supply chain, and provide a guarantee for enterprise users to safely transmit and use data with different privacy levels. This study presents a unique research paradigm that introduces the theories and methods of the new information field generation into the field of agricultural research, and thus assists in the strategy implementation of "holding grain in the land and storing grain in technology".

Promoting Re-epithelialization in an oxidative diabetic wound microenvironment using self-assembly of a ROS-responsive polymer and P311 peptide micelles.

Engineering smart nano-therapeutics for re-epithelialisation of chronic wounds facilitates the wound healing process. However, due to excessive oxidative stress damage and persistent inflammation in diabetic wound microenvironment, the migration of stimulating epidermal cells in diabetic wounds represents a significant challenge. Here we synthesised P311-loaded micelles by self-assembly of P311 peptides and diblock copolymer poly (ethylene glycol)-block-poly (propylene sulfide) (PEG-b-PPS, denoted as PEPS) that have unique ability to transform an oxidative wound microenvironment into a proregenerative one while also providing cues for epidermal cell migration. The P311@PEPS showed an accelerated migration of epidermal cells via activation of the Akt signalling pathway, simultaneously suppressing the unfavourable oxidative wound microenvironment by scavenging reactive oxygen species (ROS), ultimately leading to the induction of an environment conducive to cell migration. Furthermore, the micelles were able to bypass the inhibitory effect of ROS on the Akt signalling pathway, thereby promoting epidermal cell migration. Additionally, we observed that diabetic wounds treated with P311@PEPS showed accelerated chronic wound healing, granulation tissue formation, collagen deposition and re-epithelialisation, thereby suggesting the efficacy of P311@PEPS as a promising nanoplatform for the treatment of chronic wounds. STATEMENT OF SIGNIFICANCE: Based on the unique conditions of the diabetic wound microenvironment, a smart drug delivery system with ROS-responsive nanomaterials has been widely investigated to enhance diabetic wound healing. In our previous studies, we observed that P311 promotes epidermal cell migration to induce wound re-epithelialisation. However, the application of P311 suffers from its instability. Herein, we developed a therapeutic platform with P311-loaded micelles (P311@PEPS), which were synthesized by the self-assembly of P311 peptides and diblock copolymer poly (ethylene glycol)-block-poly (propylene sulfide) (PEG-b-PPS, denoted as PEPS). These micelles provide continuous migration signals for epidermal cells by ROS-trigged P311 release. Additionally, P311@PEPS scavenges excess ROS and provides a microenvironment that reduces inflammation, which could protect P311 from enzymatic degradation and improve the bioavailability of P311.