Abstract The demand for organ transplantation continues to grow, since the shortage of organ donors and complications associated with existing treatments remain. A promising alternative to transplantation is the implantation of artificial organs, which can be produced using 3D bioprinting technology. This approach offers the advantage of patient-specific solutions tailored to individual needs. Patients with urethral stricture or hypospadias who are unable to urinate require urethral reconstruction, which carries risks of complications and stricture recurrence. These patients may benefit from a tissue-engineered urethra fabricated using autologous cells and 3D bioprinting. Therefore, a printer setup for tubular structures was developed for 3D-Bioplotter, and a gelatin-fibrinogen-based bioink was optimised by supplementation with GelMA to enhance mechanical properties suitable for clinical applications while maintaining cell compatibility. Tensile testing, printability, suturability, and cell viability analyses were performed to assess the outcomes of the different ink compositions. An artificial urethral graft was successfully printed, using our rod-based printer setup, and the GelMA-fibrinogen hydrogel exhibited an increase in Young's modulus compared with gelatin-fibrinogen hydrogel. Further, the 5% GelMA-fibrinogen hydrogel also exhibited good suturability and maintained cell viability after 14 days in culture. Human urothelial and smooth muscle cells developed characteristic morphologies within the print, and a 210% increase in burst pressure was observed for the urethral graft after 14 days in tissue culture, compared with the acellular graft. Our 3D bioprinted artificial urethra herein, containing an inner layer of human urothelial cells stabilised with polycaprolactone and an outer ring of smooth muscle cells, represents a significant step forward in replicating natural urethral architecture for developing grafts as new treatment options for urethral disorders.
Abstract Cryomicroneedles (cryoMNs) are an emerging transdermal drug delivery platform that relies on low-temperature manufacturing. It combines cryoprotection with minimally invasive microneedle technology, effectively maintaining the activity of thermosensitive biological therapy drugs, including cells, microbes, biomacromolecules and exosomes, overcoming the drawbacks of traditional microneedles. This review summarizes the materials, preparation methods, and wide applications of cryoMNs in cell therapy, microbial delivery, drug delivery, and wound repair. The underlying therapeutic mechanisms, current challenges, and future prospects are also discussed. In summary, cryoMNs have shown great potential in the clinical translation of biotherapeutics, and this article is intended to present valuable references for the continuous development of cryoMNs.
Abstract Electrospinning is a powerful biofabrication technique for constructing fibrous scaffolds that mimic extracellular matrix architectures. However, the process is highly nonlinear and involves strongly coupled parameters, making fiber architecture and biological performance difficult to control empirically and limits reproducibility. Most machine learning (ML) studies still focus on static correlations between processing parameters and outcomes rather than on dynamic modeling of electrospinning evolution and regulation, thereby hindering real-time, precise process control. Here, we establish a data-driven framework that links process parameters, Taylor cone geometry, and nanofiber/cell outcomes through high-speed imaging and ML. A custom image-processing pipeline is developed to automatically extract cone angle, height, and width from in situ images with improved accuracy via a rotating-ray–based geometric algorithm. Using datasets collected from three representative polymer systems (PVDF, PVB, and PEO), random forest models outperform support vector machine and minimum description length, achieving moderate-to-good prediction of Taylor cone descriptors (R²≈0.57-0.83) across varied voltages, flow rate, and needle–collector distances. We further extend this framework to PEO-based cell electrospinning. By correlating predicted cone geometries with experimentally measured viability of 293T cells and umbilical cord mesenchymal stem cells, we identify a Taylor cone “safe window” that simultaneously stabilizes jet formation and preserves cell survival (>95%). Guided by this window, a bilayer cell-laden scaffold comprising a PVB support layer and a PEO–cell layer is fabricated with improved process robustness. This enables stable delivery of high-density, highly viable cells and facilitates the fabrication of three-dimensional cell-laden nanofiber scaffolds. Overall, this Taylor cone analysis, ML-guided strategy provides a quantitative framework for process-window identification in polymer and cell electrospinning, and may support future integration with real-time monitoring, online inference, and closed-loop control in intelligent biofabrication.
Abstract Cerebral organoids have emerged as advanced three-dimensional in vitro models capable of recapitulating essential aspects of human brain development, thereby offering new opportunities for studying brain physiology and disease. Nonetheless, their use in preclinical settings remains limited by their high variability. Microfluidic devices offer a promising alternative to conventional culture supports by enabling improved recapitulation of the cellular microenvironment; however, most cerebral organoids-on-chips rely on custom-made academic prototypes, limiting their scalability and translatability. Here, we established a brain organoid-on-chip model by combining a regionalized cortical organoid differentiation protocol with a commercial, standardized and industrially-compatible microfluidic device (Duplex™, NETRI). Cortical organoid quality and reproducibility were evaluated using a previously established multi-criteria Quality Control (QC) framework based on a scoring system. To enhance objectivity and throughput, the non-invasive morphometric QC criteria were automated using deep learning-based image analysis. Using a single human induced pluripotent stem cell (hiPSC) line, we assessed whether microfluidic culture conditions could improve the quality and reproducibility of cortical organoids within a controlled genetic background. Compared with conventional cultures, on-chip cortical organoids demonstrated improved inter- and intra-batch reproducibility across multiple scales, including morphology, size, cytoarchitectural organization, and transcript expression, together with higher QC scores and reduced QC failure rates. Finally, the QC framework was adapted for neurotoxicity assessment using a decision tree to classify compounds according to their neurotoxic risk. While this study represents a proof-of-concept within this cellular background, the integrated brain organoid-on-chip platform and standardized QC evaluations provide a flexible and translatable framework for preclinical and industrial studies, and may facilitate future cross-line validation of reproducible cortical organoid cultures.
Abstract During a retrospective review of our research data and published figures, we identified an inadvertent image-selection error in the assembly of Figure 4 C. Panel C(b), which was intended to show the random group, was mistakenly populated with an enlarged micrograph from the same experimental group as C(a), containing an overlapping tissue region. Consequently, the two panels did not present independent representative images of their respective experimental groups. To correct this error, panel C(a) is retained as the authentic micrograph of the nestlike group, and panel C(b) has been replaced with the authentic representative micrograph of the 4-layered CSM construct from the random group, retrieved from the original microscopy acquisition archive. In addition, in panels B(a) and B(b), the scale-bar labels have been corrected from 50 μm to 25 μm to match the scale bar in the original raw images. The multi-layered structure and collagen presence shown in Figure 4 remain fully consistent with the corrected micrographs, without altering any scientific interpretations or conclusions. The authors apologize for the errors in Figure 4.
