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Artificial biological structures hold the promise for modeling cellular assembly in vitro and have advanced considerable studies in cell biology, disease modeling, drug testing, and regenerative medicine. Biological functions are derived from micro‐ and macroscale interactions of various cell types, and a structural property matching the tissue in vivo is required to enable precision biological function. Despite various types of tissues and organs are successfully constructed by conventional biofabrication technologies, they mostly only show a small fraction of structural features found in real tissues. Tools for single‐cell manipulation provide the approach to fabricate artificial tissues cell‐by‐cell, and have enabled the construction of biological structures with single‐cell and heterogeneous features, recapitulating the complexity in vivo. This review presents a comprehensive overview of the construction of biological structures through manipulating single cells, covering single‐cell technologies with operation principles and main advances, biological structures associated with informative explanations of single‐cell manipulation during construction, and representative applications mainly focusing on analysis and modeling. Current challenges and future perspectives in this field are also discussed. [ABSTRACT FROM AUTHOR]

In the contribution at hand, a new formulation for finite strain viscosity relative to the viscous intermediate configuration is presented. The evolution of the viscous deformations is based upon a new numerical approach, which allows for a consistent consideration of anisotropic finite strain viscoelasticity, according to the authors knowledge. A standard Maxwell model is used to describe viscous behaviour at finite deformations. Furthermore, the orthotropic Yeoh material model is extended to include a distinction between behaviour under tensile and compression loading. The proposed formulation is validated, and parameters of the model are identified by material tests on Sorghum bicolor plants. Subsequently, numerical examples are shown to demonstrate the capabilities of the model. In general, the proposed Yeoh material formulation is shown to accurately represent the inability of fibres to carry compression loading. Furthermore, the viscoelastic approach, developed relative to the viscous intermediate configuration, is demonstrated to be capable of producing plausible results. Additionally, the mechanical behaviour of Sorghum bicolor plants is simulated using the introduced formulation. The results show that the contribution at hand describes a novel methodology to simulate the viscoelastic behaviour of plant materials reliably. [ABSTRACT FROM AUTHOR]

Vivid biological structures with reversible adhesive properties are widely found in nature. Although current biomimicking adhesion systems have attracted extensive attention, unmet challenges remain in terms of excellent adhesion preservation, precise structural fabrication, and good environmental compatibility. By combining advanced vat photopolymerization 3D printing technology with hydrogel materials with excellent environmental adaptability, bioinspired adhesion devices present satisfactory application prospects. Herein, a systematic overview of bioinspired hydrogel adhesion devices from the perspectives of material design, structural design, and fabrication is presented. First, the main types and application prospects of vat photopolymerization 3D printed hydrogels are introduced. Subsequently, the research progress on hydrogel‐based vat photopolymerized 3D printed bionic adhesion devices is detailed. Future developments, such as balancing unmet challenges and expected opportunities, in 3D printable multiscale bionic adhesive devices are presented. [ABSTRACT FROM AUTHOR]

A comment on how easy (or difficult) it is to find a stucture of interest and some suggestions on what could be done to start to address the problem. [ABSTRACT FROM AUTHOR]

Landmark‐based geometric morphometrics has emerged as an essential discipline for the quantitative analysis of size and shape in ecology and evolution. With the ever‐increasing density of digitized landmarks, the possible development of a fully automated method of landmark placement has attracted considerable attention. Despite the recent progress in image registration techniques, which could provide a pathway to automation, three‐dimensional (3D) morphometric data are still mainly gathered by trained experts. For the most part, the large infrastructure requirements necessary to perform image‐based registration, together with its system specificity and its overall speed, have prevented its wide dissemination.Here, we propose and implement a general and lightweight point cloud‐based approach to automatically collect high‐dimensional landmark data in 3D surfaces (Automated Landmarking through Point cloud Alignment and Correspondence Analysis). Our framework possesses several advantages compared with image‐based approaches. First, it presents comparable landmarking accuracy, despite relying on a single, random reference specimen and much sparser sampling of the structure's surface. Second, it can be efficiently run on consumer‐grade personal computers. Finally, it is general and can be applied at the intraspecific level to any biological structure of interest, regardless of whether anatomical atlases are available.Our validation procedures indicate that the method can recover intraspecific patterns of morphological variation that are largely comparable to those obtained by manual digitization, indicating that the use of an automated landmarking approach should not result in different conclusions regarding the nature of multivariate patterns of morphological variation.The proposed point cloud‐based approach has the potential to increase the scale and reproducibility of morphometrics research. To allow ALPACA to be used out‐of‐the‐box by users with no prior programming experience, we implemented it as a SlicerMorph module. SlicerMorph is an extension that enables geometric morphometrics data collection and 3D specimen analysis within the open‐source 3D Slicer biomedical visualization ecosystem. We expect that convenient access to this platform will make ALPACA broadly applicable within ecology and evolution. [ABSTRACT FROM AUTHOR]

Morphometrics has become an indispensable component of the statistical analysis of size and shape variation in biological structures. Morphometric data have traditionally been gathered through low‐throughput manual landmark annotation, which represents a significant bottleneck for morphometric‐based phenomics. Here we propose a machine‐learning‐based high‐throughput pipeline to collect high‐dimensional morphometric data in two‐dimensional images of semi‐rigid biological structures.The proposed framework has four main strengths. First, it allows for dense phenotyping with minimal impact on specimens. Second, it presents landmarking accuracy comparable to manual annotators, when applied to standardized datasets. Third, it performs data collection at speeds several orders of magnitude higher than manual annotators. And finally, it is of general applicability (i.e. not tied to a specific study system).State‐of‐the‐art validation procedures show that the method achieves low error levels when applied to three morphometric datasets of increasing complexity, with error varying from 0.57% to 2.2% of the structure's length in the automated placement of landmarks. As a benchmark for the speed of the entire automated landmarking pipeline, our framework places 23 landmarks on 13,686 objects (zooids) detected in 1,684 pictures of fossil bryozoans in 3.12 min using a personal computer.The proposed machine‐learning‐based phenotyping pipeline can greatly increase the scale, reproducibility and speed of data collection within biological research. To aid the use of the framework, we have developed a file conversion algorithm that can be used to leverage current morphometric datasets for automation, allowing the entire procedure, from model training all the way to prediction, to be performed in a matter of hours. [ABSTRACT FROM AUTHOR]