Recent advances in microfluidic technology of arterial thrombosis investigations.

Microfluidic technology has emerged as a powerful tool in studying arterial thrombosis, allowing researchers to construct artificial blood vessels and replicate the hemodynamics of blood flow. This technology has led to significant advancements in understanding thrombosis and platelet adhesion and aggregation. Microfluidic models have various types and functions, and by studying the fabrication methods and working principles of microfluidic chips, applicable methods can be selected according to specific needs. The rapid development of microfluidic integrated system and modular microfluidic system makes arterial thrombosis research more diversified and automated, but its standardization still needs to be solved urgently. One key advantage of microfluidic technology is the ability to precisely control fluid flow in microchannels and to analyze platelet behavior under different shear forces and flow rates. This allows researchers to study the physiological and pathological processes of blood flow, shedding light on the underlying mechanisms of arterial thrombosis. In conclusion, microfluidic technology has revolutionized the study of arterial thrombosis by enabling the construction of artificial blood vessels and accurately reproducing hemodynamics. In the future, microfluidics will place greater emphasis on versatility and automation, holding great promise for advancing antithrombotic therapeutic and prophylactic measures.

What is the context? To study the mechanism of arterial thrombosis, including the platelet adhesion and aggregation behavior and the coagulation process.Microfluidic technology is commonly used to study thrombosis. Microfluidic technology can simulate the real physiological environment on the microscopic scale in vitro, with high throughput, low cost, and fast speed.As an innovative experimental platform, microfluidic technology has made remarkable progress and has found applications in the fields of biology and medicine.What is new? This review summarizes the different fabrication methods of microfluidics and compares the advantages and disadvantages of these methods. Recent developments in microfluidic integrated systems and modular microfluidic systems have led to more diversified and automated microfluidic chips in the future.The different types and functions of microfluidic models are summarized. Platelet adhesion aggregation and coagulation processes, as well as arterial thrombus-related shear force changes and mechanical behaviors, were investigated by constructing artificial blood vessels and reproducing hemodynamics.Microfluidics can provide a basis for the development of personalized thrombosis treatment strategies. By analyzing the mechanism of action of existing drugs, using microfluidic technology for high-throughput screening of drugs and evaluating drug efficacy, more drug therapy possibilities can be developed.What is the impact?This review utilizes microfluidics to further advance the study of arterial thrombosis, and microfluidics is also expected to play a greater role in the biomedical field in the future.

Experimental Study on Monitoring Damage Progression of Basalt-FRP Reinforced Concrete Slabs Using Acoustic Emission and Machine Learning.

Basalt fiber-reinforced polymer (BFRP) reinforced concrete is a new alternative to conventional steel-reinforced concrete due to its high tensile strength and corrosion resistance characteristics. However, as BFRP is a brittle material, unexpected failure of concrete structures reinforced with BFRP may occur. In this study, the damage initiation and progression of BFRP-reinforced concrete slabs were monitored using the acoustic emission (AE) method as a structural health monitoring (SHM) solution. Two simply supported slabs were instrumented with an array of AE sensors in addition to a high-resolution camera, strain, and displacement sensors and then loaded until failure. The dominant damage mechanism was concrete cracking due to the over-reinforced design and adequate BFRP bar-concrete bonding. The AE method was evaluated in terms of identifying the damage initiation, progression from tensile to shear cracks, and the evolution of crack width. Unsupervised machine learning was applied to the AE data obtained from the first slab testing to develop the clusters of the damage mechanisms. The cluster results were validated using the k-means supervised learning model applied to the data obtained from the second slab. The accuracy of the K-NN model trained on the first slab was 99.2% in predicting three clusters (tensile crack, shear crack, and noise). Due to the limitation of a single indicator to characterize complex damage properties, a Statistical SHapley Additive exPlanation (SHAP) analysis was conducted to quantify the contribution of each AE feature to crack width. Based on the SHAP analysis, the AE duration had the highest correlation with the crack width. The cumulative duration of the AE sensor near the crack had close to 100% accuracy to track the crack width. It was concluded that the AE sensors positioned at the mid-span of slabs can be used as an effective SHM solution to monitor the initiation of tensile cracks, sudden changes in structural response due to major damage, damage evolution from tensile to shear cracks, and the progression of crack width.

Effect of modified washing process on water usage, composition and gelling properties of grass carp surimi.

BACKGROUND: Washing is an essential process in surimi production, from which a large amount of wastewater is generated. Due to the increasing pressure of environmental protection, it is an urgent technical requirement for surimi manufacturers to reduce water usage while maintaining the quality of surimi. In this study, composition, structure and gelling properties of grass carp surimi prepared with a modified washing process (MWP) were investigated. Intermediate dehydration with various compression ratios were utilized between two washing cycles. RESULTS: Water usage and wastewater discharge were reduced significantly by 33% and 38%, respectively, when MWP was applied. As the compression ratio increased, composition of fat, cathepsins, transglutaminase and heme proteins in surimi decreased gradually. Yield, protein content and the major protein pattern of surimi were not changed, but surface hydrophobicity gradually decreased. As the compression rate increased to 1:2.0, textural values and water holding capacity of the corresponding surimi gel decreased gradually, while whiteness increased and then remained unchanged. At a higher compression ratio (>1:1.5), aggregated network and excessive free water were observed in the surimi gel. Composition and gelling properties of the MWP surimi with a compression ratio of 1:1.2-1:1.5 were equal to those of the surimi prepared under conventional three-cycle washing. CONCLUSION: Results indicated that MWP demonstrated its great potential in surimi production by dramatically reducing the usage of cold water and discharge of wastewater without scarifying surimi quality. © 2022 Society of Chemical Industry.

Single center clinical analysis of macrophage activation syndrome complicating juvenile rheumatic diseases.

BACKGROUND: Macrophage activation syndrome (MAS), an example of secondary hemophagocytic lymphohistiocytosis, is a potentially fatal complication of rheumatic diseases. We aimed to study the clinical and laboratory characteristics, treatment schemes, and outcomes of different rheumatic disorders associated with MAS in children. Early warning indicators of MAS have also been investigated to enable clinicians to make a prompt and accurate diagnosis. METHODS: Fifty-five patients with rheumatic diseases complicated by MAS were enrolled between January 2017 and December 2022. Clinical and laboratory data were collected before disease onset, at diagnosis, and after treatment with MAS, and data were compared between patients with systemic juvenile idiopathic arthritis (sJIA), Kawasaki disease (KD), and systemic lupus erythematosus (SLE). A random forest model was established to show the importance score of each variable with a significant difference. RESULTS: Most (81.8%) instances of MAS occurred during the initial diagnosis of the underlying disease. Compared to the active stage of sJIA, the platelet count, erythrocyte sedimentation rate, and fibrinogen level in sJIA-MAS were significantly decreased, whereas ferritin, ferritin/erythrocyte sedimentation rate, aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase, and D-dimer levels were significantly increased. Ferritin level, ferritin/erythrocyte sedimentation rate, and platelet count had the greatest predictive value for sJIA-MAS. The level of IL-18 in the sJIA-MAS group was significantly higher than in the active sJIA group, whereas IL-6 levels were significantly lower. Most patients with MAS were treated with methylprednisolone pulse combined with cyclosporine, and no deaths occurred. CONCLUSIONS: Thrombocytopenia, ferritin levels, the ferritin/erythrocyte sedimentation rate, and elevated aspartate aminotransferase levels can predict the occurrence of MAS in patients with sJIA. Additionally, our analysis indicates that IL-18 plays an important role in the pathogenesis of MAS in sJIA-MAS.

Axial involvement in enthesitis-related arthritis: results from a single-center cohort.

BACKGROUND: Axial involvement in children with enthesitis-related arthritis (ERA) has characteristics that differ from those of peripheral involvement. This study characterized their clinical characteristics and treatment. METHODS: Patients with ERA at the Children's Hospital of Nanjing Medical University between January 2018 and December 2020 were included. The ERA cohort was divided into two based on the presence or absence of axial joint involvement. Demographic characteristics, clinical features, and treatments were described and compared. RESULTS: In total, 105 children with ERA were enrolled (axial ERA, n = 57; peripheral ERA, n = 48). The age at disease onset of the axial group tended to be higher (11.93 ± 1.72 vs. 11.09 ± 1.91 years) and the diagnosis delay was bigger in patients with axial ERA (10.26 ± 11.66 months vs. 5.13 ± 7.92 months). The inflammatory marker levels were significantly higher in patients with axial. There were no differences in HLA-B27 positivity between the groups (34 [59.65%] vs. 28 [58.33%], P > 0.05). Hip involvement was more frequent in the axial group (52.63% vs 27.08%; X2 = 7.033). A total of 38 (66.67%) and 10 (20.83%) patients with axial and peripheral ERA, respectively, were treated with biological disease-modifying anti-rheumatic drugs (DMARDs) at diagnosis. The administration of biologics increased gradually in the axial ERA group, peaking at 18 months and decreasing thereafter, whereas that in the peripheral ERA group peaked at 6 months and began to decline thereafter. CONCLUSIONS: Axial ERA is a persistent active disease and requires a more aggressive treatment. Classification and early recognition of axial involvement may help with timely diagnosis and appropriate management.

Effectiveness of tumor necrosis factor inhibitors in children with enthesitis-related arthritis: a single-center retrospective analysis.

Objective: In children with enthesitis-related arthritis (ERA), the hip and sacroiliac joint function might be impaired if not properly treated. We sought to evaluate the effectiveness of anti-tumor necrosis factor-α (TNF-α) therapy using the inflammatory indicators, Juvenile Arthritis Disease Activity Score 27 (JADAS27) and magnetic resonance imaging (MRI). Methods: We conducted a single-center retrospective study of 134 patients with ERA. We evaluated the effect of anti-TNF therapy on the inflammatory indicators, active joint count, MRI quantitative score, and JADAS27 over 18 months. We used the Spondyloarthritis Research Consortium of Canada (SPARCC) and the Hip Inflammation MRI Scoring System (HIMRISS) scoring systems for hip and sacroiliac joints scoring. Results: The average age of onset of children with ERA was 11.62 ± 1.95 years, and they were treated with disease-modifying antirheumatic drugs (DMARDs) combined with biologics (n = 87, 64.93%). There were no differences in HLA-B27 positivity between the biologics and non-biologics treatment groups [66 (49.25%) vs. 68 (50.75%), P > 0.05]. Children who received anti-TNF (71 received etanercept, 13 adalimumab, 2 golimumab, and 1 infliximab) therapy improved significantly. Children with ERA used DMARDs and biologics at baseline (Group A) were followed up to 18 months, and their active joint count (4.29 ± 1.99 vs. 0.76 ± 1.33, P = 0.000), JADAS27 (13.70 ± 4.80 vs. 4.53 ± 4.52, P = 0.000) and MRI quantitative scores (P = 0.001) were significantly lower than those at baseline. Some of the patients (n = 13, 9.70%) were treated with DMARDs at the onset of the disease, but did not show significant improvement (Group B). After 6-18 months of switching to anti-TNF therapy, related indicators of the children were significantly lower than at baseline and 1 month (P < 0.013). At 18 months, a total of 33 patients (n = 74, 44.59%) in Group A and 7 (n = 13, 53.85%) in Group B reached inactive state. Conclusion: Eighteen months after diagnosis, anti-TNF therapy was found to be effective in children diagnosed with ERA. MRI is important for the early diagnosis of juvenile idiopathic arthritis. TNF-α inhibitors can significantly improve the clinical manifestations of sacroiliac joint and hip involvement in patients with ERA. Overall, the real-world study provides more evidence for precision diagnosis and treatment for other hospitals, families and patients.

Physicochemical Characteristics and Flavor Properties of Texturized Dual-Proteins Extrudates: Effect of Surimi to Soybean Flour Ratio.

This study investigated the effects of surimi to soybean flour ratio (0:10, 1:9, 2:8, 3:7, 4:6) on the physicochemical characteristics and flavor properties of dual-proteins extrudates. The increasing ratio of surimi improved the color of extrudates and raised the apparent viscosity of the mixed raw materials, which led to the decrease of extrudates' thickness. The excess ratio of surimi and soybean flour (more than 2:8) was bad for extrudates' physicochemical characteristics with sharply decreased tensile strength, macroscopic longitudinal fracture, broken and unevenly distributed microstructure, increased water mobility and decreased free water content. However, the increasing ratio of surimi had no effect on the protein secondary structure of extrudates. Sensory evaluation, E-tongue and E-nose analysis suggested that adding surimi significantly changed the flavor properties of extrudates, with increased sweetness and umami taste, and an appropriate ratio (2:8 or 3:7) could reduce the beany flavor and without an obvious fishy off-flavor.

Experimental Study of the Pore Structure and Gas Desorption Characteristics of a Low-Rank Coal: Impact of Moisture.

Coal-water interactions have a prominent impact on the prediction of coal mine gas disasters and coalbed methane extraction. The change of characteristics in the microscopic pores of coal caused by the existence of water is an important factor affecting the diffusion and migration of gas in coal. The low-pressure nitrogen adsorption experiments and gas desorption experiments of a low-rank coal with different equilibrium moisture contents were conducted. The results show that both the specific surface area and pore volume decrease significantly as the moisture content increases, and the micropores (pore diameter <10 nm) are most affected by the water adsorbed by coal. In particular, for a water-equilibrated coal sample at 98% relative humidity, micropores with pore sizes smaller than 4 nm as determined by the density functional theory model almost disappear, probably due to the blocking effects of water clusters and capillary water. In this case, micropores with a diameter less than 10 nm still contribute most of the specific surface area for gas adsorption in coal. Furthermore, the fractal dimensions at relative pressures of 0-0.5 (D 1) and 0.5-1 (D 2) calculated by the Frenkel-Halsey-Hill model indicate that when the moisture content is less than 4.74%, D 1 decreases rapidly, whereas D 2 shows a slight reduction as the moisture content increased. In contrast, when the moisture content exceeds 4.74%, further increases in the moisture content cause D 2 to decrease significantly, while there is nearly no change for D 1. The correlation analyses show that the ultimate desorption volume and initial desorption rate are closely related to the fractal dimension D 1, while the desorption constant (K t) mainly depends on the fractal dimension D 2. Therefore, the gas desorption performances of coal have a close association with the pore properties of coal under water-containing conditions, which indicate that the fluctuation in moisture content should be carefully considered in the evaluation of gas diffusion and migration performances of in situ coal seams.

Robust Bayesian growth curve modelling using conditional medians.

Growth curve models have been widely used to analyse longitudinal data in social and behavioural sciences. Although growth curve models with normality assumptions are relatively easy to estimate, practical data are rarely normal. Failing to account for non-normal data may lead to unreliable model estimation and misleading statistical inference. In this work, we propose a robust approach for growth curve modelling using conditional medians that are less sensitive to outlying observations. Bayesian methods are applied for model estimation and inference. Based on the existing work on Bayesian quantile regression using asymmetric Laplace distributions, we use asymmetric Laplace distributions to convert the problem of estimating a median growth curve model into a problem of obtaining the maximum likelihood estimator for a transformed model. Monte Carlo simulation studies have been conducted to evaluate the numerical performance of the proposed approach with data containing outliers or leverage observations. The results show that the proposed approach yields more accurate and efficient parameter estimates than traditional growth curve modelling. We illustrate the application of our robust approach using conditional medians based on a real data set from the Virginia Cognitive Aging Project.