Core-shell hydrogel beads with extracellular matrix for tumor spheroid formation

Creating multicellular tumor spheroids is critical for characterizing anticancer treatments since they may provide a better model of the tumor than conventional monolayer culture. Moreover, tumor cell interaction with the extracellular matrix can determine cell organization and behavior. In this work, a microfluidic system was used to form cell-laden core-shell beads which incorporate elements of the extracellular matrix and support the formation of multicellular spheroids. The bead core (comprising a mixture of alginate, collagen, and reconstituted basement membrane, with gelation by temperature control) and shell (comprising alginate hydrogel, with gelation by ionic crosslinking) were simultaneously formed through flow focusing using a cooled flow path into the microfluidic chip. During droplet gelation, the alginate acts as a fast-gelling shell which aids in preventing droplet coalescence and in maintaining spherical droplet geometry during the slower gelation of the collagen and reconstituted basement membrane components as the beads warm up. After droplet gelation, the encapsulated MCF-7 cells proliferated to form uniform spheroids when the beads contained all three components: alginate, collagen, and reconstituted basement membrane. The dose-dependent response of the MCF-7 cell tumor spheroids to two anticancer drugs, docetaxel and tamoxifen, was compared to conventional monolayer culture.     

Unsupervised self-training correction learning for 2D image-based 3D model retrieval

Existing 2D image-based 3D model retrieval (IBMR) methods usually use the pseudo labels as semantic guidance to reduce the domain-wise and class-wise feature distribution difference across annotated 2D images and unlabeled 3D models. However, they cannot entirely guarantee the quality of pseudo labels, which will decrease prediction discriminability and diversity to affect feature distribution alignment. Therefore, we propose a novel unsupervised self-training correction learning (USTCL) network for the IBMR task. Specifically, we first utilize a CNN to encode 2D images and 3D models (described as multi-view images). Then, we design a noise-corrected self-training learning module (NCST) to denoise pseudo labels in an adversarial manner to make the predicted categories more easily discriminated to improve prediction discriminability. Besides, we employ a target-guided pseudo label refining strategy (TPLR) to progressively refine generated pseudo labels to prevent minority categories from being pushed into majority categories, thereby enhancing prediction diversity. Comprehensive experiments on popular IBMR benchmarks validate the effectiveness and robustness of USTCL, e.g., it can achieve the average gains of 54.20%/22.30%, 62.17%/43.21%, 54.21%/31.18%, 63.48%/43.28%, 59.87%/44.49% in terms of NN, FT, ST, F-measure, DCG and the decrease of 29.50%/35.15% corresponding to ANMRR on MI3DOR (21,000 2D images and 7,690 3D models) and MI3DOR-2 (19,694 2D images and 3,982 3D models), respectively.     

Instance-prototype similarity consistency for unsupervised 2D image-based 3D model retrieval

The unsupervised 3D model retrieval is designed to joint the information of well-labeled 2D domain and unlabeled 3D domain to learn collaborative representations. Most existing methods adopted semantic alignment, but were inevitably affected by false pseudo-label. In this paper, we design a novel Instance-Prototype Similarity Consistency Network (IPSC) to guide domain alignment with similarity consistency, which can simultaneously suppress the impact of false pseudo-label information and well reduce the domain discrepancy. IPSC contains two similarity strategies, named Single instance vs Multiple prototypes and Instance-pair vs Single prototype. The first strategy utilizes a single instance as an anchor, and measures the similarities between the anchor and multiple prototypes with the same category but from different domains. The minimization between these similarities can better align the cross-domain prototypes with Kullback–Leibler (KL) divergence than traditional Euclidean similarities. The second strategy utilizes a single prototype as an anchor, and measures the similarities between this anchor and an instance-pair with the same category but from different domains. The minimization between these similarities can conduct the instance-level alignment with KL divergence, which can better suppress the negative effect of noisy pseudo-labels. We conduct various experiments on two datasets, MI3DOR-1 (21000 2D images and 7690 3D models) and MI3DOR-2 (19694 2D images and 3982 3D models), to verify the superiority of our algorithm.     

An integrated microfluidic bubble pocket for long-term perfused three-dimensional intestine-on-a-chip model

Perfused three-dimensional (3D) cultures enable long-term in situ growth and monitoring of 3D organoids making them well-suited for investigating organoid development, growth, and function. One of the limitations of this long-term on-chip perfused 3D culture is unintended and disruptive air bubbles. To overcome this obstacle, we invented an imaging platform that integrates an innovative microfluidic bubble pocket for long-term perfused 3D culture of gastrointestinal (GI) organoids. We successfully applied 3D printing technology to create polymer molds that cast polydimethylsiloxane (PDMS) culture chambers in addition to bubble pockets. Our developed platform traps unintended, or induced, air bubbles in an integrated PDMS pocket chamber, where the bubbles diffuse out across the gas permeable PDMS or an outlet tube. We demonstrated that our robust platform integrated with the novel bubble pocket effectively circumvents the development of bubbles into human and mouse GI organoid cultures during long-term perfused time-course imaging. Our platform with the innovative integrated bubble pocket is ideally suited for studies requiring long-term perfusion monitoring of organ growth and morphogenesis as well as function.     

A review on 3D printing functional brain model

Modern neuroscience increasingly relies on 3D models to study neural circuitry, nerve regeneration, and neural disease. Several different biofabrication approaches have been explored to create 3D neural tissue model structures. Among them, 3D bioprinting has shown to have great potential to emerge as a high-throughput/high precision biofabrication strategy that can address the growing need for 3D neural models. Here, we have reviewed the design principles for neural tissue engineering. The main challenge to adapt printing technologies for biofabrication of neural tissue models is the development of neural bioink, i.e., a biomaterial with printability and gelation properties and also suitable for neural tissue culture. This review shines light on a vast range of biomaterials as well as the fundamentals of 3D neural tissue printing. Also, advances in 3D bioprinting technologies are reviewed especially for bioprinted neural models. Finally, the techniques used to evaluate the fabricated 2D and 3D neural models are discussed and compared in terms of feasibility and functionality.     

基于ArcScene和SketchUp的流域三维模型建立

流域三维可视化是“数字流域”中的一个重要组成部分,流域三维可视化作为一种新的管理方法和技术手段在流域管理中越来越体现其重要性。本文以构建漓江流域三维可视化场景为例,提出了一种采用ArcScene和Google SketchUp软件,快速有效地构建三维流域的方法。     

城市三维模型海量数据动态组织调度方法

城市三维模型的海量特性和当前计算机硬件瓶颈给模型的实时渲染提出了较大的挑战.改进三维地理信息系统(GIS)中数据的组织与管理方式是提高三维场景可视化效率的有效途径,本文提出基于四叉树空间索引对数据进行组织,基于视点的层次模型技术(LOD)对数据进行动态调度,同时提出一种将纹理作为渲染单元重构网格数据的方法,对粗糙模型的渲染进行批处理,有效降低了耗时的渲染次数.实验证明,该方法是高效可行的,渲染帧率稳定在30帧左右,能够满足海量城市三维模型的可视化和实时交互需求.     

A microfluidic model for organ-specific extravasation of circulating tumor cells

Circulating tumor cells (CTCs) are the principal vehicle for the spread of non-hematologic cancer disease from a primary tumor, involving extravasation of CTCs across blood vessel walls, to form secondary tumors in remote organs. Herein, a polydimethylsiloxane-based microfluidic system is developed and characterized for in vitro systematic studies of organ-specific extravasation of CTCs. The system recapitulates the two major aspects of the in vivo extravasation microenvironment: local signaling chemokine gradients in a vessel with an endothelial monolayer. The parameters controlling the locally stable chemokine gradients, flow rate, and initial chemokine concentration are investigated experimentally and numerically. The microchannel surface treatment effect on the confluency and adhesion of the endothelial monolayer under applied shear flow has also been characterized experimentally. Further, the conditions for driving a suspension of CTCs through the microfluidic system are discussed while simultaneously maintaining both the local chemokine gradients and the confluent endothelial monolayer. Finally, the microfluidic system is utilized to demonstrate extravasation of MDA-MB-231 cancer cells in the presence of CXCL12 chemokine gradients. Consistent with the hypothesis of organ-specific extravasation, control experiments are presented to substantiate the observation that the MDA-MB-231 cell migration is attributed to chemotaxis rather than a random process.     

基于三维结构模型的TID动力分析

在探讨技术创新扩散(TID)动力和影响因素之间区别的基础上,构建技术创新扩散主体的三维结构模型,并基于该模型分析技术创新扩散的主动方面,得出基本结论。     

Image-based 3D model retrieval via disentangled feature learning and enhanced semantic alignment

With the development of 3D technology and the increase in 3D models, 2D image-based 3D model retrieval tasks have drawn increased attention from scholars. Previous works align cross-domain features via adversarial domain alignment and semantic alignment. However, the extracted features of previous methods are disturbed by the residual domain-specific features, and the lack of labels for 3D models makes the semantic alignment challenging. Therefore, we propose disentangled feature learning associated with enhanced semantic alignment to address these problems. On one hand, the disentangled feature learning enables decoupling the twisted raw features into the isolated domain-invariant and domain-specific features, and the domain-specific features will be dropped while performing adversarial domain alignment and semantic alignment to acquire domain-invariant features. On the other hand, we mine the semantic consistency by compacting each 3D model sample and its nearest neighbors to further enhance semantic alignment for unlabeled 3D model domain. We give comprehensive experiments on two public datasets, and the results demonstrate the superiority of the proposed method. Especially on MI3DOR-2 dataset, our method outperforms the current state-of-the-art methods with gains of 2.88% for the strictest retrieval metric NN.     

基于3DS与OpenGL的三维人体模型构建方法

在应用程序中构建三维人体模型是实现三维虚拟试衣系统的一项基础工作。在Visual C＋＋6.0开发环境下,利用OpenGL和3DS优势互补实现人体模型的构建和交互。克服了因OpenGL没有提供三维模型的高级命令,仅通过点、线及多边形等基本几何图元构建模型所造成的工作量和难度大的问题,实现了快速构建高质量三维人体模型的目的。     

Optimal control and pattern formation for a haptotaxis model of solid tumor invasion

This paper deal with an optimal control problem for a haptotaxis model of solid tumor invasion by considering the multiple treatments of cancer (a combination of radiotherapy and chemotherapy). Firstly, we obtain the existence and uniqueness of weak solution for the controlled system with spatial dimensions $N=1,2,3$ by applying the Leray–Schauder fixed point theorem and developing adapted a priori estimates. Subsequently, the existence of optimal pair are proved by means of the technique of minimizing sequence. Furthermore, we verify the Lipschitz continuity of control-to-state mapping based on some a priori estimates, hence derive the first-order necessary optimality condition and establish the optimality systems. Finally, the ringlike diffusion and aggregation patterns and the dynamics of tumor invasion as well as the optimal control strategies are presented numerically, which demonstrate that the optimal treatment strategies are capable of breaking the pattern formation, and preventing the tumor invading and metastasizing, even eliminating the tumor possibly. The results of this work improved and extended previous results partially.     

3D打印技术对著作权制度的冲击与回应

3D打印技术的出现对著作权制度产生了巨大冲击,它不仅加剧了明确作品"复制"行为范围的迫切性,动摇了"合理使用"限制中部分规定的必要性,还使得对于"技术中立"原则引致侵权责任减免的合理性受到质疑。为回应相关技术发展带来的挑战,结合《集成电路布图设计保护条例》保护模式对比探讨,认为有必要适时拓宽"复制"行为范围,进一步规范"合理使用"的行使,创新技术管理模式以完善著作权制度。     

Rational design of high-quality 2D/3D perovskite heterostructure crystals for record-performance polarization-sensitive photodetection

Polarization-sensitive photodetection is central to optics applications and has been successfully demonstrated in photodetectors of two-dimensional (2D) materials, such as layered hybrid perovskites; however, achieving high polarization sensitivity in such a photodetector remains extremely challenging. Here, for the first time, we demonstrate a high-performance polarization-sensitive photodetector using single-crystalline 2D/3D perovskite heterostructure, namely, (4-AMP)(MA)₂Pb₃Br₁₀/MAPbBr₃ (MA = methylammonium; 4-AMP = 4-(aminomethyl)piperidinium), which exhibits ultrahigh polarization sensitivity up to 17.6 under self-driven mode. To our knowledge, such a high polarization selectivity has surpassed all of the reported perovskite-based devices, and is comparable to, or even better than, the traditional inorganic heterostructure-based photodetectors. Further studies reveal that the built-in electric field formed at the junction can spatially separate the photogenerated electrons and holes, reducing their recombination rate and thus enhancing the performance for polarization-sensitive photodetection. This work provides a new source of polarization-sensitive materials and insights into designing novel optoelectronic devices.     

优化地球三维有限元计算网格的一种方法

在研究大尺度的三维地球动力学问题的数值模拟过程中，往往需要对整个球体或部分球壳生成计算网格，而且网格单元的尺寸对所研究的问题尤为重要。计算网格既满足地球物理分析的需要，又要避免内部网格过小的浪费。本文提出了一种地球结构化网格的生成和加密划分方案，可以对整个球体形成较为均匀的网格，并对近地表的区域能够完成网格加密以达到地球物理分析的需要。生成的网格在简单的试算中得到了优异的结果。     

多基线SAR三维成像的QR分解算法

根据多基线合成孔径雷达(SAR)三维成像的信号模型,得到了利用高度向观测数据实现目标三维成像的矩阵方程,并引入QR分解算法求解矩阵方程,形成了多基线SAR三维成像的QR分解算法.使用该算法对多基线SAR仿真数据进行了三维成像实验.     

WSN中一种改进的三维DV-Hop节点定位算法

本文在研究传统的DV-Hop3D算法基础上提出了一种新无线传感器网络定位算法。新算法在算法的第一阶段设置了跳数阈值参数以减小通信开销,并且在算法的第二阶段用可选择的平均跳距代替固定的平均跳距来计算未知节点到锚节点的距离,最后用Matlab7.1进行了仿真。仿真结果表明,该改进算法可明显提高节点定位精度,并且能有效降低网络通信量。     

3D打印技术的应用对企业创新独占的挑战与对策研究

综述了3D打印技术的原理和发展现状,并探讨了该技术的应用对企业创新独占以及创新独占机制的挑战,随后采用案例研究方法,对12家国内外企业展开调研,提出了企业应对由于该技术的应用带来的创新独占挑战的具体策略。