Designing Microgels for Cell Culture and Controlled Assembly of Tissue Microenvironments

Micrometer‐sized hydrogels, termed microgels, are emerging as multifunctional platforms that can recapitulate tissue heterogeneity in engineered cell microenvironments. The microgels can function as either individual cell culture units or can be assembled into larger scaffolds. In this manner, individual microgels can be customized for single or multicell coculture applications, or heterogeneous populations can be used as building blocks to create microporous assembled scaffolds that more closely mimic tissue heterogeneities. The inherent versatility of these materials allows user‐defined control of the microenvironments, from the order of singly encapsulated cells to entire 3D cell scaffolds. These hydrogel scaffolds are promising for moving towards personalized medicine approaches and recapitulating the multifaceted microenvironments that exist in vivo.     

From Arteries to Capillaries: Approaches to Engineering Human Vasculature

From microscaled capillaries to millimeter‐sized vessels, human vasculature spans multiple scales and cell types. The convergence of bioengineering, materials science, and stem cell biology has enabled tissue engineers to recreate the structure and function of different hierarchical levels of the vascular tree. Engineering large‐scale vessels aims to replace damaged arteries, arterioles, and venules and their routine application in the clinic may become a reality in the near future. Strategies to engineer meso‐ and microvasculature are extensively explored to generate models for studying vascular biology, drug transport, and disease progression as well as for vascularizing engineered tissues for regenerative medicine. However, bioengineering tissues for transplantation has failed to result in clinical translation due to the lack of proper integrated vasculature for effective oxygen and nutrient delivery. The development of strategies to generate multiscale vascular networks and their direct anastomosis to host vasculature would greatly benefit this formidable goal. In this review, design considerations and technologies for engineering millimeter‐, meso‐, and microscale vessels are discussed. Examples of recent state‐of‐the‐art strategies to engineer multiscale vasculature are also provided. Finally, key challenges limiting the translation of vascularized tissues are identified and perspectives on future directions for exploration are presented.     

4D Printing of a Bioinspired Microneedle Array with Backward‐Facing Barbs for Enhanced Tissue Adhesion

Microneedle (MN), a miniaturized needle with a length‐scale of hundreds of micrometers, has received a great deal of attention because of its minimally invasive, pain‐free, and easy‐to‐use nature. However, a major challenge for controlled long‐term drug delivery or biosensing using MN is its low tissue adhesion. Although microscopic structures with high tissue adhesion are found from living creatures in nature (e.g., microhooks of parasites, barbed stingers of honeybees, quills of porcupines), creating MNs with such complex microscopic features is still challenging with traditional fabrication methods. Here, a MN with bioinspired backward‐facing curved barbs for enhanced tissue adhesion, manufactured by a digital light processing 3D printing technique, is presented. Backward‐facing barbs on a MN are created by desolvation‐induced deformation utilizing cross‐linking density gradient in a photocurable polymer. Barb thickness and bending curvature are controlled by printing parameters and material composition. It is demonstrated that tissue adhesion of a backward‐facing barbed MN is 18 times stronger than that of barbless MN. Also demonstrated is sustained drug release with barbed MNs in tissue. Improved tissue adhesion of the bioinspired MN allows for more stable and robust performance for drug delivery, biofluid collection, and biosensing.     

Porous Silicon Nanoparticles Embedded in Poly(lactic‐co‐glycolic acid) Nanofiber Scaffolds Deliver Neurotrophic Payloads to Enhance Neuronal Growth

Scaffolds made from biocompatible polymers provide physical cues to direct the extension of neurites and to encourage repair of damaged nerves. The inclusion of neurotrophic payloads in these scaffolds can substantially enhance regrowth and repair processes. However, many promising neurotrophic candidates are excluded from this approach due to incompatibilities with the polymer or with the polymer processing conditions. This work provides one solution to this problem by incorporating porous silicon nanoparticles (pSiNPs) that are preloaded with the therapeutic into a polymer scaffold during fabrication. The nanoparticle‐drug‐polymer hybrids are prepared in the form of oriented poly(lactic‐co‐glycolic acid) nanofiber scaffolds. Three different therapeutic payloads are tested: bpV(HOpic), a small molecule inhibitor of phosphatase and tensin homolog (PTEN); an RNA aptamer specific to tropomyosin‐related kinase receptor type B (TrkB); and the protein nerve growth factor (NGF). Each therapeutic is loaded using a loading chemistry that is optimized to slow the rate of release of these water‐soluble payloads. The drug‐loaded pSiNP‐nanofiber hybrids release approximately half of their TrkB aptamer, bpV(HOpic), or NGF payload in 2, 10, and >40 days, respectively. The nanofiber hybrids increase neurite extension relative to drug‐free control nanofibers in a dorsal root ganglion explant assay.     

Advanced Theragenerative Biomaterials with Therapeutic and Regeneration Multifunctionality

All tissues and organs can be affected by diseases, and treatments for these diseases can cause damage to surrounding healthy tissues and organs. Therefore, treatment is required that involves disease therapy alongside tissue/organ regeneration. The design, construction, and biomedical applications of biomaterial platforms with both disease‐therapeutic and tissue‐regeneration multifunctionalities are in demand, which are herein referred to as theragenerative (abbreviation of therapy and regeneration) biomaterials. Due to the rapid development of theragenerative biomaterials in versatile biomedical applications, this progress report aims to summarize, discuss, and highlight the rational construction of distinctive theragenerative biomaterials with intrinsic therapeutic performance and tissue‐regeneration bioactivity. Based on the intrinsic response to either external physical triggers (e.g., photonic response or magnetic‐field response) or endogenous disease microenvironments (e.g., mild acidity or overexpressed hydrogen peroxide) and tissue‐regeneration bioactivity, these theragenerative biomaterials are extensively explored in various biomedical fields, including bone‐tumor therapy/regeneration, bone antibacterial therapy/regeneration, skin‐tumor therapy/regeneration, skin antibacterial therapy/regeneration, breast‐tumor therapy/adipose‐tissue regeneration, and osteoarticular‐tuberculosis therapy/bone‐tissue regeneration. The challenges faced and future developments of these distinctive theragenerative biomaterials are discussed, as are methods for further promoting their clinical translation.     

Automatic Buffer Overflow Warning Validation

Static buffer overflow detection techniques tend to report too many false positives fundamentally due to the lack of software execution information. It is very time consuming to manually inspect all the static warnings. In this paper, we propose BovInspector, a framework for automatically validating static buffer overflow warnings and providing suggestions for automatic repair of true buffer overflow warnings for C programs. Given the program source code and the static buffer overflow warnings, BovInspector first performs warning reachability analysis. Then, BovInspector executes the source code symbolically under the guidance of reachable warnings. Each reachable warning is validated and classified by checking whether all the path conditions and the buffer overflow constraints can be satisfied simultaneously. For each validated true warning, BovInspector provides suggestions to automatically repair it with 11 repair strategies. BovInspector is complementary to prior static buffer overflow discovery schemes. Experimental results on real open source programs show that BovInspector can automatically validate on average 60% of total warnings reported by static tools.

     

救灾物资高维多目标自适应分配问题建模与求解

针对救灾物资分配中效率和公平性的均衡问题,提出一种基于二维整数编码的高维多目标自适应分配算法。首先构建了一个综合考虑应急响应总时间、灾民恐慌度、救灾物资未满足度、物资分配公平性、灾民损失、应急响应总成本的高维多目标优化模型,然后采用二维整数编码和自适应个体修正（AIR）解决潜在的应急资源冲突,最后引入移位密度估计和第二代强度帕累托进化算法（SPEA2）设计了一个救灾物资高维多目标分配算法。在仿真实验中,与带有编码修正机制的非支配排序差异演化算法（ERNS-DE）和基于贪心搜索的多目标遗传算法（GSMOGA）相比,所提算法在两种应急环境中的覆盖值分别提高了34.87%、100%和23.59%、100%,同时所提算法的超体积值也远远高于两种对比算法。实验结果表明,所提模型和算法可以让决策者根据实际应急需求选择应急方案,具有更好的灵活性和求解效率。     

基于条件生成对抗网络的乳腺上皮和间质区域自动分割

乳腺病理组织图像中上皮和间质区域的自动分割对乳腺癌的诊断和治疗具有非常重要的临床意义。但是由于乳腺组织病理图像中上皮和间质区域具有高度复杂性,因此一般的分割模型很难只根据提供的分割标记来有效地训练,并对两种区域进行快速、准确的分割。为此,提出一种基于条件对抗网络（cGAN）的上皮和间质分割条件对抗网络（EPScGAN）模型。在EPScGAN中,判别器的判别机制为生成器的训练提供了一个可训练的损失函数,来更加准确地衡量出生成器网络的分割结果输出和真实标记之间的误差,从而更好地指导生成器的训练。从荷兰癌症研究所（NKI）和温哥华综合医院（VGH）两个机构提供的专家标记的乳腺病理图像数据集中随机裁剪出1 286张尺寸为512×512的图像作为实验数据集,然后将该数据集按照7：3的比例划分为训练集和测试集对EPScGAN模型进行训练和测试。结果表明,EPScGAN模型在测试集的平均交并比（mIoU）为78.12%,和其他6种流行的深度学习分割模型相比较,提出的EPScGAN具有更好的分割性能。