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Abstract Given the complexity of issuing, verifying, and trading green power certificates in China, along with the challenges posed by policy changes, ensuring that China’s green certificate market trading system receives proper mechanisms and technical support is crucial. This study presents a green power certificate trading (GC-TS) architecture based on an equilibrium strategy, which enhances the quoting efficiency and multi-party collaboration capability of green certificate trading by introducing Q-learning, smart contracts, and effectively integrating a multi-agent trading Nash strategy. Firstly, we integrate green certificate trading with electricity and carbon asset trading, constructing pricing strategies for the green certificate, carbon, and electricity trading markets; secondly, we design a certificate-electricity-carbon efficiency model based on ensuring the consistency of green certificates, green electricity, and carbon markets; then, to achieve diversified green certificate trading, we establish a multi-agent reinforcement learning game equilibrium model. Additionally, we propose an integrated Nash Q-learning offer with a smart contract dynamic trading joint clearing mechanism. Experiments show that trading prices have increased by 20%, and the transaction success rate by 30 times, with an analysis of trading performance from groups of 3, 5, 7, and 9 trading agents exhibiting high consistency and redundancy. Compared with models integrating smart contracts, it possesses a higher convergence efficiency of trading quotes.

Fusarium crown rot (FCR) is an important and devastating disease of wheat (Triticum aestivum) caused by the fungus Fusarium pseudograminearum and related pathogens. Using two distinct susceptible cultivars, we investigated the isolation frequencies of F. pseudograminearum and quantified its biomass accumulation and the levels of the associated toxins deoxynivalenol (DON) and DON-3-glucoside (D3G) in inoculated field-grown wheat plants. We detected F. pseudograminearum in stem, peduncle, rachis, and husk tissues, but not in grains, whereas DON and D3G accumulated in stem, rachis, husk, and grain tissues. Disease severity was positively correlated with the frequency of pathogen isolation, F. pseudograminearum biomass, and mycotoxin levels. The amount of F. pseudograminearum biomass and mycotoxin contents in asymptomatic tissue of diseased plants were associated with the distance of the tissue from the diseased internode and the disease severity of the plant. Thus, apparently healthy tissue may harbor F. pseudograminearum and contain associated mycotoxins. This research helps clarify the relationship between F. pseudograminearum occurrence, F. pseudograminearum biomass, and mycotoxin accumulation in tissues of susceptible wheat cultivars with or without disease symptoms, providing information that can lead to more effective control measures.

Abstract The objective of this retrospective study was to predict short-term efficacy of anti-vascular endothelial growth factor (VEGF) treatment in diabetic macular edema (DME) using machine learning regression models. Real-world data from 279 DME patients who received anti-VEGF treatment at Ineye Hospital of Chengdu University of TCM between April 2017 and November 2022 were analyzed. Eight machine learning regression models were established to predict four clinical efficacy indicators. The accuracy of the models was evaluated using mean absolute error (MAE), mean square error (MSE) and coefficient of determination score (R 2). Multilayer perceptron had the highest R 2 and lowest MAE among all models. Regression tree and lasso regression had similar R 2, with lasso having lower MAE and MSE. Ridge regression, linear regression, support vector machines and polynomial regression had lower R 2 and higher MAE. Support vector machine had the lowest MSE, while polynomial regression had the highest MSE. Stochastic gradient descent had the lowest R 2 and high MAE and MSE. The results indicate that machine learning regression algorithms are valuable and effective in predicting short-term efficacy in DME patients through anti-VEGF treatment, and the lasso regression is the most effective ML algorithm for developing predictive regression models.

Background: In recent years, baroreflex activation therapy (BAT) has been utilized to treat heart failure with reduced ejection fraction (HFrEF). However, the supporting literature on its efficacy and safety is still limited. This investigation elucidates the effects of BAT in HFrEF patients to provide a reference for future clinical applications. Methods: This investigation follows Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines. Relevant investigations on the use of BAT in HFrEF patients were searched and selected from 5 databases, including Web of Science, MEDLINE, PubMed, Embase, and Cochrane Library, from inception to December 2022. The methodological quality of eligible articles was assessed via the Cochrane risk of bias tool, and for meta-analysis, RevMan (5.3) was used. Results: Randomized controlled trials comprising 343 participants were selected for the meta-analysis, which revealed that in HFrEF patients, BAT enhanced the levels of LVEF (MD: 2.97, 95 % CI: 0.53 to 5.41), MLHFQ (MD: −14.81, 95 % CI: −19.57 to −10.06) and 6MWT (MD: 68.18, 95 % CI: 51.62 to 84.74), whereas reduced the levels of LVEDV (MD: −15.79, 95 % CI: −32.96 to 1.37) and DBP (MD: −2.43, 95 % CI: −4.18 to −0.68). Conclusion: It was concluded that BAT is an efficient treatment option for HFrEF patients. However, to validate this investigation, further randomized clinical trials with multiple centers and large sample sizes are needed.

The process of hole seeding on the mulch during full-film double-row furrow corn planting faces issues such as poor seed discharge and seed blockage. To address these challenges, a pendulum-lever-type hole-forming mechanism is designed, along with an adjustment device. By analyzing the working principles of the pendulum-lever-type hole seeder and the adjustment device, the structural parameters of the device are determined. Through theoretical analysis and simulation experiments, three-dimensional models of seeds and hole seeders are constructed. Based on MBD-DEM cosimulation, the trajectory of seed movement and the seeding process of the hole seeder are analyzed to elucidate the effects of the hole-former opening and the number of pendulum bearings on seeding quality. To improve the operational performance of the hole seeder, experiments are conducted using the hole seeder’s rotating disc speed, lever angle of the hole-former, and the number of pendulum bearings as experimental factors, with the qualification index, miss-seeding index, and reseeding index as experimental indicators. A three-factor, three-level Box–Behnken central composite experiment is performed to obtain mathematical models of the relationships between the experimental factors and indicators. Using Design-Expert 12 software, the regression models are optimized for multiple objectives to obtain the optimal parameter combination: a seeder disc speed of 49 r/min (corresponding to a forward speed of 5.76 km/h), a lever angle of 131°, and four pendulum bearings. Under this optimal parameter combination, the qualification index is 91.70%, the miss-seeding index is 4.57%, and the reseeding index is 3.73%. Experimental validation of the seeding performance of the hole seeder under the optimal parameter combination is conducted. Bench tests show that the qualification index, miss-seeding index, and reseeding index are 90.53%, 5.60%, and 3.87%, respectively. Field tests demonstrate a qualification index of 89.13%, a miss-seeding index of 5.46%, and a reseeding index of 6.41%. The actual results are consistent with the optimized values, providing valuable insights for the design and performance optimization of hole seeders.

With the improvement in living standards and growing appreciation for flaxseed’s nutritional value, global demand for flaxseed and its economic significance are continuously increasing. As a major flaxseed producer and exporter, China plays a crucial role in the development of its agricultural economy. Flaxseed, one of China’s five key oil crops, is renowned for its rich nutritional content. This study employed a literature review to systematically examine the research status of key flaxseed dehulling technologies in China. It explored the characteristics, efficiencies, and quality differences among various dehulling methods, while also drawing on advanced techniques, such as chemical and ultrasonic dehulling, to provide new perspectives and theoretical support for flaxseed dehulling. Comprehensive analysis revealed that mechanical dehulling (the impact method and rolling and rubbing method) is the primary method used in China. The study also identified the issues in current flaxseed dehulling research in China and offers suggestions to guide future improvements and innovations in flaxseed processing, aiming to enhance the quality and nutritional value of flaxseed to meet diverse market demands.

To conduct an in-depth investigation of the impact of various operating parameters on mulching device wear during the operation of full-film dual-row ridging and mulching machine mulching, this paper employed EDEM software to create a 3D discrete element model of how a mulching device interacts with the soil on the seed bed and simulated the dynamic process of the interaction between the mulching device and the soil during the mulching operation. We analyzed the cladding wear process between the cladding device and the cladding sand particles, and two areas of impact wear on the overburden conveyor housing and areas of wear on the chute deflector scratches were detected. A three-factor, three-level Box–Behnken experimental design approach was used, with mathematical modeling of the relationship between the scraper conveyor lifting line speed, seed bed cover, scraper spacing, and wear of the cover device, finding the optimal combination of operating parameters for mulching devices. The results of the simulation test indicated that the mulching device experienced a minimum wear of 0.958 × 10−3 mm at a lifting line speed of 0.7 m·s−1 for the scraper conveyor, a mulching volume of 2.55 kg·s−1 for the seed bed, and a scraper spacing of 98 mm. The results of the field trial validation showed that, in a comparison between simulated wear parts and a mulching operation prototype of the same two wear parts, the established discrete element model appeared reasonable concerning the structural parameters, with a feasible abrasion mechanism process of sand particles on the soil-covering devices, demonstrating the model’s reliability and validity. It can serve as a guide for optimizing the design of mechanized full-film dual-furrow seed bed mulching operation.

Water is an important factor limiting the development of arid rain-fed agriculture. Film mulching is an effective way to ensure yield in arid areas. However, whether biodegradable film can be used instead of polyethylene film for agricultural production in arid areas is a matter of contention. In this study, AquaCrop model simulation and field experiment were used to analyze the production effect of corn whole film double ridge furrow sowing technology covering polyethylene film (PM) and biodegradable film (BM) in Dingxi City from 2016 to 2020. The results showed that the AquaCrop simulation data have a high fitting with the field test data, and the model was suitable for simulating dry farming in Dingxi City. The best sowing time in Dingxi City is to select the average temperature to be stable at about 15 °C (around 15 April to 25 April each year), and the yield is the highest after sowing during this period. Although BM can achieve environmental protection and energy saving, it is weaker than PM in water storage and soil evaporation inhibition in arid areas. The average yield, aboveground biomass, water productivity, and harvest index of PM were 63.95%, 18.57%, 76.35%, and 38.22% higher than those of BM, respectively. In drought years, BM water stress on leaf expansion, induced stomatal closure, and premature senescence were 61%, 17%, and 9.5% higher than PM, respectively, and the stress time was 28.5 d, 5 d, and 26 d, respectively. The maximum canopy coverage and effective root zone water content were 24.5% and 30.49% lower, respectively. In the wet year, water stress under BM only had a certain effect on the leaf expansion of crops but had no effect on the induction of stomatal closure and premature senescence. The maximum canopy coverage and effective root zone water content were 13.56% and 31.35% lower, respectively. The above studies show that BM has a certain ability to store water and preserve moisture, but the parameters of PM are better than BM. Especially in dry years, the crop production efficiency of PM is more significant. It can be seen that in rain-fed agricultural areas with rainfall less than 500 mm, biodegradable film can not replace polyethylene film.

BackgroundThe pathogenesis of myocardial infarction complicating depression is still not fully understood. Bioinformatics is an effective method to study the shared pathogenesis of multiple diseases and has important application value in myocardial infarction complicating depression.MethodsThe differentially expressed genes (DEGs) between control group and myocardial infarction group (M-DEGs), control group and depression group (D-DEGs) were identified in the training set. M-DEGs and D-DEGs were intersected to obtain DEGs shared by the two diseases (S-DEGs). The GO, KEGG, GSEA and correlation analysis were conducted to analyze the function of DEGs. The biological function differences of myocardial infarction and depression were analyzed by GSVA and immune cell infiltration analysis. Four machine learning methods, nomogram, ROC analysis, calibration curve and decision curve were conducted to identify hub S-DEGs and predict depression risk. The unsupervised cluster analysis was constructed to identify myocardial infarction molecular subtype clusters based on hub S-DEGs. Finally, the value of these genes was verified in the validation set, and blood samples were collected for RT-qPCR experiments to further verify the changes in expression levels of these genes in myocardial infarction and depression.ResultsA total of 803 M-DEGs, 214 D-DEGs, 13 S-DEGs and 6 hub S-DEGs (CD24, CSTA, EXTL3, RPS7, SLC25A5 and ZMAT3) were obtained in the training set and they were all involved in immune inflammatory response. The GSVA and immune cell infiltration analysis results also suggested that immune inflammation may be the shared pathogenesis of myocardial infarction and depression. The diagnostic models based on 6 hub S-DEGs found that these genes showed satisfactory combined diagnostic performance for depression. Then, two molecular subtypes clusters of myocardial infarction were identified, many differences in immune inflammation related-biological functions were found between them, and the hub S-DEGs had satisfactory molecular subtypes identification performance. Finally, the analysis results of the validation set further confirmed the value of these hub genes, and the RT-qPCR results of blood samples further confirmed the expression levels of these hub genes in myocardial infarction and depression.ConclusionImmune inflammation may be the shared pathogenesis of myocardial infarction and depression. Meanwhile, hub S-DEGs may be potential biomarkers for the diagnosis and molecular subtype identification of myocardial infarction and depression.

Chaetomium globosum is a common plant endophytic fungi that exhibits great biocontrol potential in plant disease. Fusarium crown rot (FCR) is an important disease in wheat that seriously threatens wheat production worldwide. The control effect of C. globosum against wheat FCR remains unclear. In this study, we introduced an identified C. globosum 12XP1-2-3 and tested its biological control potential against wheat FCR. The hypha and fermentation broth exhibited an antagonistic effect against Fusarium pseudograminearum. Results from indoor experiments showed that C. globosum 12XP1-2-3 might delay the onset of symptoms of brown stem base and significantly reduced the disease index (37.3%). Field trials showed that wheat seeds coated with a spore suspension of 12XP1-2-3 grew better than the control seeds, had control effects of 25.9–73.1% on FCR disease, and increased wheat yield by 3.2–11.9%. Analysis of rhizosphere microorganisms revealed that seeds coated with C. globosum (‘Cg’ treatment) had a greater effect on fungal rather than on bacterial alpha diversity and may improve the health state of rhizosphere microorganisms, as reflected by the significantly increased fungal Shannon index at Feekes 11 and the increased complexity of the bacterial co-occurrence network but decreased complexity of the fungal network. Moreover, the accumulation of beneficial bacteria such as Bacillus and Rhizobium at Feekes 3, and Sphingomonas at Feekes 7 in the ‘Cg’ treatment may be the important contributions to healthier wheat growth state, significantly reduced relative abundance of Fusarium at Feekes 11, and reduced occurrence of FCR disease. These results provide a basis for further research on the mechanism of action of C. globosum and its application in the biological control of FCR in the field.

The aim of this study was to investigate the effects of different working parameters on the cleaning efficiency of a cleaning device during the separation and cleaning process in a flax joint harvesting machine. To achieve this objective, CFD–DEM joint simulation technology was used to construct a CFD model of the cleaning device and a DEM model of the discharged flax material; the simulation results show the flax cleaning process. The Box–Behnken experimental design method was used to establish a mathematical model between the vibrating sieve frequency, vibrating sieve amplitude, fan wind speed, seed impurity rate, and cleaning loss rate to find the optimum combination of cleaning equipment parameters and to conduct a field verification test. The simulation test results show that, when the vibrating sieve frequency is 6 Hz, the vibrating sieve amplitude is 14.42 mm, the fan wind speed is 5.96 m/s, and the machine cleaning effect is the best; the simulation test was measured following a seed impurity rate of 2.97% and cleaning loss rate of 2.17%. The field test verification results show that, after optimizing the working parameters of the cleaning device, the cleaning loss rate is 3.58% and the impurity rate of the grain combine harvester is 3.16%, thus meeting the national and industry requirements. The test results and simulation results are highly consistent with the model, thereby verifying the reliability of the model. The results of the study provide a reference for the design and performance optimization of the flax combine cleaner.

ObjectiveTo evaluate the diagnostic accuracy of deep learning algorithms to identify age-related macular degeneration and to explore factors impacting the results for future model training.MethodsDiagnostic accuracy studies published in PubMed, EMBASE, the Cochrane Library, and ClinicalTrails.gov before 11 August 2022 which employed deep learning for age-related macular degeneration detection were identified and extracted by two independent researchers. Sensitivity analysis, subgroup, and meta-regression were performed by Review Manager 5.4.1, Meta-disc 1.4, and Stata 16.0. The risk of bias was assessed using QUADAS-2. The review was registered (PROSPERO CRD42022352753).ResultsThe pooled sensitivity and specificity in this meta-analysis were 94% (P = 0, 95% CI 0.94-0.94, I2 = 99.7%) and 97% (P = 0, 95% CI 0.97-0.97, I2 = 99.6%), respectively. The pooled positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and the area under the curve value were 21.77(95% CI 15.49-30.59), 0.06 (95% CI 0.04-0.09), 342.41 (95% CI 210.31-557.49), and 0.9925, respectively. Meta-regression indicated that types of AMD (P = 0.1882, RDOR = 36.03) and layers of the network (P = 0.4878, RDOR = 0.74) contributed to the heterogeneity.ConclusionsConvolutional neural networks are mostly adopted deep learning algorithms in age-related macular degeneration detection. Convolutional neural networks, especially ResNets, are effective in detecting age-related macular degeneration with high diagnostic accuracy. Types of age-related macular degeneration and layers of the network are the two essential factors that impact the model training process. Proper layers of the network will make the model more reliable. More datasets established by new diagnostic methods will be used to train deep learning models in the future, which will benefit for fundus application screening, long-range medical treatment, and reducing the workload of physicians.

Lipid droplets are the major organelles for fat storage in a cell and analyzing lipid droplets in Caenorhabditis elegans (C. elegans) can shed light on obesity-related diseases in humans. In this work, we propose to use a label free scattering-based method, namely dark field microscopy, to visualize the lipid droplets with high contrast, followed by deep learning to perform automatic segmentation. Our method works through combining epi-illumination dark field microscopy, which provides high spatial resolution, with asymmetric illumination, which computationally rejects multiple scattering. Due to the raw data’s high quality, only 25 images are required to train a Convolutional Neural Network (CNN) to successfully segment lipid droplets in dense regions of the worm. The performance is validated on both healthy worms as well as those in starvation conditions, which alter the size and abundance of lipid droplets. Asymmetric illumination substantially improves CNN accuracy compared with standard dark field imaging from 70% to be 85%, respectively. Meanwhile, standard segmentation methods such as watershed and DIC object tracking (DICOT) failed to segment droplets due to the images’ complex label-free background. By successfully analyzing lipid droplets in vivo and without staining, our method liberates researchers from dependence on genetically modified strains. Further, due to the “open top” of our epi-illumination microscope, our method can be naturally integrated with microfluidic chips to perform large scale and automatic analysis.

The agronomic technology of whole plastic-film mulching on double ridges has been widely promoted in the arid region of northwest China, which has caused serious residual film pollution in the field. Mechanized residual plastic-film collecting is the main way, but this way of residual plastic-film collecting is more complicated. To prove the effect of typical film-lifting parts on residual plastic-film collecting performance by a numerical simulation method, further evaluate and select the working parts suitable for residual plastic-film collecting and improve the collecting efficiency, virtual whole plastic-film mulching on double ridges needs to be established. In this study, the film-lifting parts and the double ridge with flexible, deformable, mulching, film interaction model was developed using the discrete element method (DEM). The interaction model was used to simulate the operation process of a typical third-order shovel, hug plate and elastic teeth film-lifting parts. Furthermore, the operation resistance, seed bed disturbance and collecting residual film form under different working conditions were analyzed. The simulation results show that: the disturbance of the ridge from strong to weak is the third-order shovel, elastic teeth and hug plate film-lifting parts; the crushing of the ridge soil from strong to weak is the elastic teeth, the hug plate and the third-order shovel film-lifting parts; the collecting film from strong to weak is the hug plate, elastic teeth and the third-order shovel film-lifting parts; the median value of the horizontal force fluctuation range of the ridge soil on the film-lifting parts is increased, and the increase trend is from large to small in the third-order shovel, elastic teeth and hug plate film-lifting parts (the third-order shovel is 5250 N, 6250 N and 7750 N; the hug plate is 3250 N, 3500 N and 4000 N; and the elastic teeth are 4150 N, 4550 N and 5450 N). The comparative analysis results show that the hug plate film-lifting parts are more suitable for the residual-film collecting of whole plastic-film mulching on double ridges. Field trials were carried out to verify the operational effectiveness of the hug plate film-lifting parts. The results show that the morphological changes of the recovered residual film and the simulated mulching film during the operation of the hug plate-type residual film machine, and the distribution of the surface properties of the ridge after the residual-film collecting are basically consistent with the simulation results, and the film pick-up rate of hug plate film-lifting parts reaches 95.20%, and the established discrete element interaction model is reliable. The research results can provide reference for the research and development of full film duopoly furrow-mechanized residual film-collecting agricultural equipment in the arid region of northwest China.

China is a large flax-growing country, with planting area and production ranking among the top three in the world. However, the cultivation range of flax in China is very broad, complex, and diverse, resulting in different planting scales and patterns, making it difficult to apply foreign large combine harvesters, and China lacks a dedicated flax combine harvester. This research improved the design of the 4LZ-4.0 crawler-type flax combine harvester for the regional features and flax cropping patterns in China. First, the structure, technical parameters, and working principles of the machine were introduced; second, the theoretical analysis and optimization of key components were performed; and finally, with the advancing speed of the machine, the speed of the threshing drum, and the speed of the suction fan as independent variables and the rate of removal and the total loss rate as response values, a three-factor, three-level response surface analysis method was used. For each component and response value, a mathematical model was created, and the factors and their interactions were evaluated and confirmed. The results demonstrated that the three parameters impact the threshing drum speed, advancing speed, and centrifugal fan speed in that order of priority, as well as the total loss rate in that order of priority. The machine’s optimal operating settings were 1.5 m·s−1 advancing speed, 788.49 r·min−1 threshing drum speed, and 885.34 r·min−1 centrifugal fan speed, and the validation test results indicated that under the typical dryland dense flax cultivation mode, it had a 97.46% threshing rate and 2.99% total loss rate after the test. This demonstrated that optimizing operational parameters may decrease losses in the process of mechanical flax harvesting, enhance harvesting efficiency, and satisfy the marketable flax harvesting standards.

Abstract Background Viral myocarditis (VMC) is a type of cardiac inflammation that is generally caused by coxsackievirus B3 (CVB3) infection. Several MicroRNAs (miRNAs) are known to play crucial roles in VMC pathogenesis. MiR-15 is reportedly associated with myocardial injury, inflammatory responses and viral infection. Whether miR-15 affects the occurrence and development of VMC remains largely unknown. The roles of miR-15 and their underlying mechanisms in CVB3-stimulated H9c2 cells were assessed in this study. Methods We infected H9c2 cells with CVB3 to establish a VMC cellular model. We then determined the effects of miR-15 inhibition on three cardiomyocyte injury markers: lactate dehydrogenase (LDH), creatine kinase-MB (CK-MB) and cardiac troponin-I (cTn-I). The impact on CVB3-induced cell apoptosis and pro-inflammatory cytokines was also investigated. The effects of miR-15 inhibition on NLRP3 inflammasome activation were also assessed. The target relationship between miR-15 and NOD-like receptor X1 (NLRX1) was determined using a luciferase reporter assay. Results MiR-15 expression was significantly upregulated in H9c2 cells after CVB3 infection. Inhibition of miR-15 significantly decreased the CVB3-induced levels of LDH, CK-MB and cTn-I. It also elevated cell viability, reduced CVB3-induced cell apoptosis and decreased the generation of the interleukins IL-1β, IL-6 and IL-18. Furthermore, we determined that miR-15 inhibition suppressed NLRP3 inflammasome activation by downregulating NLRP3 and caspase-1 p20 expression. We found a direct target relationship between miR-15 and NLRX1. Additionally, inhibition of NLRX1 reversed the protective effects of miR-15 inhibition against CVB3-induced myocardial cell injury by regulating the NLRP3 inflammasome. Conclusion Our results indicate that miR-15 inhibition alleviates CVB3-induced myocardial inflammation and cell injury. This may be partially due to NLRX1-mediated NLRP3 inflammasome inactivation.

Ferroptosis is a form of cell death induced by excess iron and accumulation of reactive oxygen species in cells. Recently, ferroptosis has been reported to be associated with cancer and ischemia/reperfusion (I/R) injury in multiple organs. However, the regulatory effects and underlying mechanisms of myocardial I/R injury are not well-understood. The role of miR-135b-3p as an oncogene that accelerates tumor development has been confirmed; however, its role in myocardial I/R is not fully understood. In this study, we established an in vivo myocardial I/R rat model and an in vitro hypoxia/reoxygenation (H/R)-induced H9C2 cardiomyocyte injury model and observed that ferroptosis occurred in tissues and cells during I/R myocardial injury. We used database analysis to find miR-135b-3p and validated its inhibitory effect on the ferroptosis-related gene glutathione peroxidase 4 (Gpx4), using a luciferase reporter assay. Furthermore, miR-135b-3p was found to promote the myocardial I/R injury by downregulating GPX4 expression. The results of this study elucidate a novel function of miR-135b-3p in exacerbating cardiomyocyte ferroptosis, providing a new therapeutic target for improving I/R injury.

α-lactalbumin was modified by ultrasound (US, 20 kHz, 43 ± 3.4 W/cm−2) pre-treatments (0, 15, 30 and 60 min) and laccase cross-linking of sonicated α-lactalbumin was used to evaluate the physical and oxidative stability of conjugated linoleic acid (CLA) emulsions. The emulsions prepared with laccase cross-linking US-α-lactalbumin (α-lactalbumin treated with US pre-treatment) and US-α-lactalbumin were scrutinized for oxidative and physical stability at room temperature for two weeks of storage. Laccase cross-linking US-α-lactalbumin (Lac-US-α-lactalbumin) revealed improved physical stability in comparison with US-α-lactalbumin, specified by droplet size, structural morphology, adsorbed protein, emulsifying properties and creaming index. SDS-PAGE analysis showed that there was formation of polymers in Lac-US-α-lactalbumin emulsion. Surface hydrophobicity of Lac-US-α-lactalbumin was higher than that of US-α-lactalbumin, and gradually enhanced with the increase of ultrasound time. More importantly, the measurements of peroxide values and conjugated dienes were used to study the oxidative stability of the CLA emulsions. The Lac-US-α-lactalbumin emulsion proved to be reducing the synthesis of fatty acid hydroperoxides and less conjugated dienes compared to the native and US-α-lactalbumin emulsions. This study revealed that the combination of US pre-treatment and laccase cross-linking might be an effective technique for the modification of CLA emulsions.

Background and Purpose: Patients' self-perceived burden (SPB) is associated with distress, which has a potentially negative influence on disease rehabilitation and quality of life. Stroke represents a significant health and social burden. The aim of the study was to assess, compare, and identify predictors of SPB in stroke survivors during the first 3 months post-stroke.Methods: A prospective longitudinal study was used. Consecutive stroke inpatients were recruited from the neurology department of three general hospitals in Xi'an, China. Patients were surveyed using the Self-perceived Burden Scale (SPBS) on the fourth day of admission (Acute phase, Time 1, T1) and 1 month (Time 2, T2) and 3 months (Time 3, T3) post-stroke.Results: Considerable burden was experienced by 84.15–91.50% of patients in the first 3 months post-stroke. The mean score of physical burden was the highest. Over time, physical, emotional, and economic burden all declined. The following characteristics had significant association with increased patient SPB at T1, T2, and T3: age, self-evaluated economic pressure, comorbidity, and functional status (P < 0.01). Patients' knowledge about stroke was only significantly associated with SPB at T3 (P < 0.01).Conclusions: Patients experienced a high degree of SPB in the early stage after stroke. Addressing the characteristics and predicting factors as well as the development of a targeted intervention for SPB may improve survival and post-stroke disability.