Organ‐ and tissue‐level biological functions are intimately linked to microscale cell–cell interactions and to the overarching tissue architecture. Together, biofabrication and organoid technologies offer the unique potential to engineer multi‐scale living constructs, with cellular microenvironments formed by stem cell self‐assembled structures embedded in customizable bioprinted geometries. This study introduces the volumetric bioprinting of complex organoid‐laden constructs, which capture key functions of the human liver. Volumetric bioprinting via optical tomography shapes organoid‐laden gelatin hydrogels into complex centimeter‐scale 3D structures in under 20 s. Optically tuned bioresins enable refractive index matching of specific intracellular structures, countering the disruptive impact of cell‐mediated light scattering on printing resolution. This layerless, nozzle‐free technique poses no harmful mechanical stresses on organoids, resulting in superior viability and morphology preservation post‐printing. Bioprinted organoids undergo hepatocytic differentiation showing albumin synthesis, liver‐specific enzyme activity, and remarkably acquired native‐like polarization. Organoids embedded within low stiffness gelatins (<2 kPa) are bioprinted into mathematically defined lattices with varying degrees of pore network tortuosity, and cultured under perfusion. These structures act as metabolic biofactories in which liver‐specific ammonia detoxification can be enhanced by the architectural profile of the constructs. This technology opens up new possibilities for regenerative medicine and personalized drug testing.

3D printing has revolutionized the manufacturing of volumetric components and structures in many areas. Several fully volumetric light‐based techniques have been recently developed thanks to the advent of photocurable resins, promising to reach unprecedented short print time (down to a few tens of seconds) while keeping a good resolution (around 100 μm). However, these new approaches only work with homogeneous and relatively transparent resins so that the light patterns used for photo‐polymerization are not scrambled along their propagation. Herein, a method that takes into account light scattering in the resin prior to computing projection patterns is proposed. Using a tomographic volumetric printer, it is experimentally demonstrated that implementation of this correction is critical when printing objects whose size exceeds the scattering mean free path. To show the broad applicability of the technique, functional objects of high print fidelity are fabricated in hard organic scattering acrylates and soft cell‐laden hydrogels (at 4 million cells mL −1 ). This opens up promising perspectives in printing inside turbid materials with particular interesting applications for bioprinting cell‐laden constructs.

Volumetric Bioprinting Volumetric bioprinting shapes organoid‐laden constructs into centimeter‐scale assemblies that mimic native liver function. In article number 2110054, Riccardo Levato and co‐workers report the development of a hydrogel‐based bioresin with tunable optical properties to minimize scattering in light‐based printing and ensure high resolution. Organoid viability and maturation is preserved by the shear‐stress‐free printing, and salient liver functions mature in response to the 3D bioprinted architecture.

Glioblastoma (GBM) is the most prevalent type of primary brain tumor. Treatment options include maximal surgical resection and drug-radiotherapy combination. However, patient prognosis remains very poor, prompting the search for new models for drug discovery and testing, especially those that allow assessment of in vivo responses to treatment. Zebrafish xenograft models have an enormous potential to study tumor behavior, proliferation and cellular interactions. Here, an in vivo imaging and proliferation assessment method of human GBM xenograft in zebrafish larvae is introduced. Zebrafish larvae microinjected with fluorescently labeled human GBM cells were screened daily using a stereomicroscope and imaged by light sheet fluorescence microscopy (LSFM); volumetric modeling and composite reconstructions were done in single individuals. Larvae containing tumors were enzymatically dissociated, and proliferation of cancer cells was measured using dye dilution by flow cytometry. GBM micro-tumors formed mainly in the zebrafish yolk sac and perivitelline space following injection in the yolk sac, with an engraftment rate of 73%. Daily image analysis suggested cellular division, as micro-tumors progressively grew with differentiated fluorescence intensity signals. Using dye dilution assay by flow cytometry, at least three GBM cells' division cycles were identified. The combination of LSFM and flow cytometry allows assessment of proliferation and tumor growth of human GBM inside zebrafish, making it a useful model to identify effective anti-proliferative agents in a preclinical setting.

Over the past decades, ceramics have attracted much interest for their superior properties, including hardness, durability, and stability in extreme environments. They meet fabrication needs in various fields ranging from transportation industry (e.g., diesel engines) to the energy sector (e.g., nuclear) but also environment, defense, aerospace, and in the medical sector (e.g., ceramic thermal barrier coatings, filters, lightweight space mirrors, hip or knee implants). [1][2][3][4][5][6] However, the fabrication of complex ceramic parts remains very challenging. Mainly because of their hardness and brittleness, conventional manufacturing processes, such as machining or molding, are limited to simple object geometries as well as being costly and time-consuming. Additive manufacturing (AM) represents an attractive alternative. Not only does it offer more flexibility in terms of architecture and significantly reduce material waste but also it leads to cost-effective production in a shorter time. In the liquid-based AM technologies being used for the fabrication of ceramics, the process starts with a liquid preceramic polymer (PCP) that is first solidified into a 3D object: the so-called green body. The latter is then transformed into a ceramic material, generally denoted as polymer-derived ceramic (PDC), through a pyrolysis step. [7] Initially, PCP resins were processed or shaped using conventional polymer-forming techniques such as injection molding or extrusion. Later, it was demonstrated that by adding a photoinitiator to the liquid precursor, the solid green body can be formed by exposure to UV radiation. [8] Through photopolymerization, laser-based stereolithography (SLA) has enabled the fabrication of PCP components with high resolution and a good surface quality. [9] It consists of scanning a laser beam on the photosensitive PCP resin and selectively hardening the material, building the 3D green body

3D Printing in Scattering Materials Volumetric tomographic additive manufacturing fabricates centimeter‐scale devices in seconds. In article number 2105144 , Christophe Moser and co‐workers report a method to control light in scattering materials and ensure high print quality. Using this method, they demonstrate the light‐based fabrication of complex geometries in acrylic resins loaded with TiO 2 and of hollow unobstructed channels in cell‐laden hydrogels, emulating vasculature.

We identified photopolymers for 2-photon polymerisation with biocompatibility for human iPSC-derived neural network development. Generation of microscale scaffold topologies enabled neurite guidance, demonstrating use in reproducing aligned networks.

Massive molecular testing for COVID-19 has been pointed out as fundamental to moderate the spread of the pandemic. Pooling methods can enhance testing efficiency, but they are viable only at low incidences of the disease. We propose Smart Pooling, a machine learning method that uses clinical and sociodemographic data from patients to increase the efficiency of informed Dorfman testing for COVID-19 by arranging samples into all-negative pools. To do this, we ran an automated method to train numerous machine learning models on a retrospective dataset from more than 8000 patients tested for SARS-CoV-2 from April to July 2020 in Bogotá, Colombia. We estimated the efficiency gains of using the predictor to support Dorfman testing by simulating the outcome of tests. We also computed the attainable efficiency gains of non-adaptive pooling schemes mathematically. Moreover, we measured the false-negative error rates in detecting the ORF1ab and N genes of the virus in RT-qPCR dilutions. Finally, we presented the efficiency gains of using our proposed pooling scheme on proof-of-concept pooled tests. We believe Smart Pooling will be efficient for optimizing massive testing of SARS-CoV-2.