It is well known that three-dimensional (3D) printing is an emerging technology used to produce customized implants and surface characteristics of implants, strongly deciding their osseointegration ability. In this study, Ti alloy microspheres were printed under selected rational printing parameters in order to tailor the surface micro-characteristics of the printed implants during additive manufacturing by an in situ, controlled way. The laser path and hatching space were responsible for the appearance of the stripy structure (S), while the bulbous structure (B) and bulbous–stripy composite surface (BS) were determined by contour scanning. A nano-sized structure could be superposed by hydrothermal treatment. The cytocompatibility was evaluated by culturing Mouse calvaria-derived preosteoblastic cells (MC3T3-E1). The results showed that three typical microstructured surfaces, S, B, and BS, could be achieved by varying the 3D printing parameters. Moreover, the osteogenic differentiation potential of the S, B, and BS surfaces could be significantly enhanced, and the addition of nano-sized structures could be further improved. The BS surface with nano-sized structure demonstrated the optimum osteogenic differentiation potential. The present research demonstrated an in situ, controlled way to tailor and optimize the surface structures in micro-size during the 3D printing process for an implant with higher osseointegration ability.

The main aim of this paper is to achieve the suitable SA-GEL (sodium alginate and gelatin) porous cartilage scaffold by 3D printing technology with optimal prediction parameters. Firstly, the characteristics of SA-GEL were analyzed, the influence of calcium chloride on the gel was explored, and the optimal cross-linking concentration and gelation temperature were determined. Secondly, a prediction model of the extrusion line width of SA-GEL was established, in which the printing pressure, the moving speed of the needle and the fiber interval were the important parameters affecting the printing performance of the SA-GEL composite material. Thirdly, the SA-GEL composite scaffolds were printed on the Bio-plotter platform, the C5.18 chondrocytes cells were cultured in the SA-GEL biomaterial scaffold, and the results show that the cells could survive well. These results show that, under the control of the printing parameters pressure 1.8 bar, moving speed 10.7 mm/s and the internal structure parameters of the scaffold is 0/45-1.2 (Printing interval: 1.2 mm, angle value: 45 degree), SA-GEL scaffold printing results can be obtained which have good mechanical properties and biocompatibility.

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Bacterial infection caused by biomaterials is a very serious problem in the clinical treatment of implants. The emergence of antibiotic resistance has prompted other antibacterial agents to replace traditional antibiotics. Silver is rapidly developing as an antibacterial candidate material to inhibit bone infections due to its significant advantages such as high antibacterial timeliness, high antibacterial efficiency, and less susceptibility to bacterial resistance. However, silver has strong cytotoxicity, which can cause inflammatory reactions and oxidative stress, thereby destroying tissue regeneration, making the application of silver‐containing biomaterials extremely challenging. In this paper, the application of silver in biomaterials is reviewed, focusing on the following three issues: 1) how to ensure the excellent antibacterial properties of silver, and not easy to cause bacterial resistance; 2) how to choose the appropriate method to combine silver with biomaterials; 3) how to make silver‐containing biomaterials in hard tissue implants have further research. Following a brief introduction, the discussion focuses on the application of silver‐containing biomaterials, with an emphasis on the effects of silver on the physicochemical properties, structural properties, and biological properties of biomaterials. Finally, the review concludes with the authors’ perspectives on the challenges and future directions of silver in commercialization and in‐depth research.

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Most tissue‐engineered blood vessels are endothelialized by static cultures in vitro. However, it has not been clear whether endothelial cell‐shedding and local damage may occur in an endothelial layer formed by static cultures under the effect of blood flow shear postimplantation. In this study, we report a bionic and cost‐effective vascular chip platform, and proved that a static culture of endothelialized tissue‐engineered blood vessels had the problem of a large number of endothelial cells falling off under the condition imitating the human arterial blood flow, and we addressed this challenge by regulating the flow field in a vascular chip. Electrospun membranes made of highly oriented or randomly distributed poly(ε‐caprolactone) fibers were used as the vascular scaffolds, on which endothelial cells proliferated well and eventually formed dense intima layers. We noted that the monolayers gradually adapted to the artery‐like microenvironment through the regulation of chip flow field, which also revealed improved cellular orientations. In conclusion, we have proposed a vascular chip with adaptive flow patterns to gradually accommodate the statically cultured vascular endothelia to the shear environment of arterial flow field and enhanced the orientation of the endothelial cells. This strategy may find numerous potential applications such as screening of vascular engineering biomaterials and maturation parameters, studying of vascular biology and pathology, and construction of vessel‐on‐a‐chip models for drug analysis, among others.

In the marine environment, underwater targets are often affected by interference from other targets and environmental fluctuations, so traditional target tracking methods are difficult to use for tracking underwater targets stably and accurately. Among the traditional methods, the Kalman filtering method is widely used; however, it only has advantages in solving linear problems and it is difficult to use to realize effective tracking problems when the trajectory of the moving target is nonlinear. Aiming to solve this limitation, an LSTM–Kalman filtering method was proposed, which can efficiently solve the problem of overly large deviations in underwater target tracking. Using this method, we first studied the features of typical underwater targets and, according to these rules, constructed the corresponding target dataset. Second, we built a convolutional neural network (CNN) model to detect the target and determine the tracking value of the moving target. We used a long-term and short-term memory artificial neural network (LSTM-NN) to modify the Kalman filter to predict the azimuth and distance of the target and to update it iteratively. Then, we verified the new method using simulation tests and the measured data from an acoustic sea trial. The results showed that compared to the traditional Kalman filtering method, the relative error of the LSTM–Kalman filtering method was reduced by 60% in the simulation tests and 72.25% in the sea trial and that the estimation variance was only 4.79. These results indicate that the method that is proposed in this paper achieves good prediction results and a high prediction efficiency for underwater target tracking.

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