Rapid fabrication of modular 3D paper-basedmicrofluidic chips using projection-based 3D printing

Paper-based microchips have different advantages,such as better biocompatibility,simple production,and easy handling,making them promising candidates for clinical diagnosis and other fields.This study describes amethod developed to fabricate modular three-dimensional(3D)paper-based microfluidic chips based on projection-based 3D printing(PBP)technology.A series of two-dimensional(2D)paper-based microfluidic modules was designed and fabricated.After evaluating the effect of exposure time on the accuracy of the flow channel,the resolution of this channel was experimentally analyzed.Furthermore,several 3D paper-based microfluidic chips were assembled based on the 2D ones using different methods,with good channel connectivity.Scaffold-based 2D and hydrogel-based 3D cell culture systems based on 3D paper-based microfluidic chips were verified to be feasible.Furthermore,by combining extrusion 3D bioprinting technology and the proposed 3D paper-based microfluidic chips,multiorgan microfluidic chips were established by directly printing 3D hydrogel structures on 3D paperbased microfluidic chips,confirming that the prepared modular 3D paper-based microfluidic chip is potentially applicable in various biomedical applications.

Rapid printing of 3D porous scaffolds for breast reconstruction

Prosthesis implantation and fat transplantation are common breast reconstructionmethods.In general,prosthesis implantation alone does not achieve a realistic enough appearance,and fat transplantation alone is difficult to achieve in the correct capacity.To date,no reports have focused on methods of combining fat with implanted prostheses for breast reconstruction.Using a newly designed bionic ink(i.e.,polyether F127 diacrylate(F127DA)&poly(ethylene glycol)diacrylate(PEGDA))and projection-based three-dimensional bioprinting(PBP),we report the development of a new method for printing porous prostheses.PEGDA was used to improve the printing precision of the prosthesis by increasing the gel point of F127DA and reducing the impact of external temperature.The compression modulus of the printed prosthesis was very close to that of prostheses currently used in clinical practice and to that of natural breasts.Finally,stromal vascular fraction gel(SVF-gel),a human fat extract,was injected into the pores of the synthesized prostheses to prepare a prosthesis mixed with adipose tissue.These were implanted subcutaneously in nude mice to observe their biological performance.After 14 and 28 days of observation,the prosthesis showed good biocompatibility,and adipose tissues grew well in and around the prosthesis.This result shows that a porous prosthesis containing pre-placed adipose tissues is a promising breast reconstruction material.

A high-precision image classification network model based on a voting mechanism

With the development of satellite remote sensing technology,image classification task,as the basis of remote sensing data interpretation,has received wide attention to improving accuracy and robustness.At the same time,in-depth learning technology has been widely used in remote sensing and has a far-reaching impact.Since the existing image classification methods ignore the feature that the general image semantics are the same as the semantics of a single pixel,this paper presents an algorithm that uses the semantics of an image to achieve high-precision image classification.Based on the idea of partial substitution for global,this algorithm designs a split result voting mechanism and builds a Vgg-Vote network model.This mechanism votes on the semantically segmented result of an image and uses the maximum filtering function to select the category containing the most significant number of pixels as the prediction category of the image.Experiments on UC Merced Land-User complete datasets and five types of incomplete datasets with varying degrees of interference,including noise,data occlusion and loss,show that the Vote mechanism dramatically improves the classification accuracy,robustness and anti-jamming capability of Vgg-Vote.