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In order to clarify the effect of the non-catalytic carbohydrate-binding module (CBM) and F5/8 type C domains on the enzymatic properties of AlgL7, an alginate lyase from Microbulbifer sp. ALW1, the full-length enzyme AlgL7 and two truncated enzymes: CD1 (catalytic domain) and CD2 (containing F5/8 type C domain and catalytic domain) were constructed and characterized. The results showed that the truncated enzyme CD2 exhibited higher specific activity, thermostability, Michaelis constant (Km), and maximum reaction velocity (Vmax) compared to the full-length AlgL7, indicating that the CBM domain played an important role in maintaining the substrate affinity of the enzyme, but reduced the catalytic activity, thermostability, and Vmax value the enzyme. Compared to the truncated enzyme CD1, CD2 exhibited higher specific activity, optimal reaction temperature, thermostability, Vmax, and Km, indicating that the F5/8 type C domain contributed to improve the enzymatic activity, optimum reaction temperature, thermostability, and Vmax, but reduced the substrate affinity of the enzyme. Using sodium alginate as the substrate, the specific activity of CD2 was 183.9 U/mg. The optimal reaction temperature and pH were 40 ℃ and 7.0, respectively. The Km and Vmax were 39.80 mg/mL and 2 000 U/mg, respectively. The major enzymatic hydrolysates were disaccharides and trisaccharides. This study promotes the understanding of the structure-activity relationship between the non-catalytic domains and the properties of alginate lyase, and lays a theoretical basis for using the non-catalytic domains to improve the catalytic properties of alginate lysate.

In this study, the total sugar, protein, 3,6-anhydro galactose and sulfate contents, apparent molecular mass and monosaccharide composition of porphyran isolated from Porphyra yezoensis were analyzed. The pro-angiogenic activity and underlying mechanism of porphyran were further investigated using human umbilical vein endothelial cells (HUVECs) as an in vitro angiogenesis model. The effect of porphyran on the cell viability of HUVECs was determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Cell adhesion and migration capacity were evaluated using cell adhesion and wound healing assays. The number of lumens formed by HUVECs was analyzed using in vitro tube formation assay. The expression levels of E-cadherin and N-cadherin in HUVECs were analyzed by Western Blotting, and the pro-angiogenic mechanism of porphyran in HUVECs was explored using specific inhibitors of mitogen-activated protein kinases (MAPKs) and vascular endothelial growth factor (VEGF) receptor tyrosine kinase inhibitors. The results showed that porphyran contained (77.48 ± 2.62)% total sugar, (3.24 ± 0.58)% protein, and (20.30 ± 1.06)% 3,6-anhydrogalactose as well as (20.78 ± 3.31)% sulfate groups. The apparent molecular mass of porphyran was 39.81 kDa. Porphyran was mainly composed of galactose, 3,6-anhydrogalactose and sulfate groups, suggesting it to be a sulfated galactan. Furthermore, porphyran treatment in the concentration range of 0–200 μg/mL had no significant toxicity no HUVECs, but instead promote cell proliferation, adhesion, migration, and vascular network formation. Further studies demonstrated that porphyran exerted its pro-angiogenic effect primarily by mediating the down-regulation of E-cadherin expression and the up-regulation of N-cadherin expression through the c-Jun N-terminal kinase (JNK) MAPK and VEGF receptor signaling pathways. In conclusion, porphyran has pro-angiogenic potential, which will provide a scientific basis for the development of porphyran as a novel pro-angiogenic factor and the precision nutrition-guided deep processing and high-value utilization of the red seaweed P. yezoensis.

The composite electromagnetic linear actuator features a co-axial integrated design that merges the moving coil and moving iron actuator types. This design leads to significant interactions among electrical, magnetic, and thermal fields during operation, which in turn affect energy consumption and temperature increases. To further improve the material utilization rate of the actuator and optimize its comprehensive performance, such as force density and temperature rise, a multi-physical field collaborative optimization method was proposed. First, the energy consumption and temperature rise mechanisms of the actuator were analyzed. The bidirectional coupling relationships of multi-physical fields during its operation are studied. Simulations and experiments were conducted to establish the rules governing the spatiotemporal evolution of energy consumption and temperature fluctuations under standard operational conditions. Based on this, a system-level collaborative optimization model for the actuator was established. Sensitivity analysis helped segregate the design variables into system-level and independent categories. Subsequently, using a multi-objective genetic algorithm, the optimal parameter settings were determined. The optimization results revealed that the force constant of the main driving components increased by 5.4%, and the average temperature of the coil decreased by 6.3%; additionally, the starting force of auxiliary components increased by 2.3%, and the temperature of the yoke decreased by 0.8%. [ABSTRACT FROM AUTHOR]

The work function is the key surface property that determines the energy required to extract an electron from the surface of a material. This property is crucial for thermionic energy conversion, band alignment in heterostructures, and electron emission devices. This work presents a high‐throughput workflow using density functional theory (DFT) to calculate the work function and cleavage energy of 33,631 slabs (58,332 work functions) that are created from 3,716 bulk materials. The number of calculated surface properties surpasses the previously largest database by a factor of ≈27. Several surfaces with an ultra‐low (<2 eV) and ultra‐high (>7 eV) work function are identified. Specifically, the (100)‐Ba‐O surface of BaMoO3 and the (001)‐F surface of Ag2F have record‐low (1.25 eV) and record‐high (9.06 eV) steady‐state work functions. Based on this database a physics‐based approach to featurize surfaces is utilized to predict the work function. The random forest model achieves a test mean absolute error (MAE) of 0.09 eV, comparable to the accuracy of DFT. This surrogate model enables rapid predictions of the work function (≈ 105 faster than DFT) across a vast chemical space and facilitates the discovery of material surfaces with extreme work functions for energy conversion and electronic device applications. [ABSTRACT FROM AUTHOR]