A microarray platform designed for high-throughput screening the reaction conditions for the synthesis of micro/nanosized biomedical materials

Optimization of a tunable process for rapid production of calcium phosphate microparticles using a droplet-based microfluidic platform

Calcium phosphate (CaP) biomaterials are amongst the most widely used synthetic bone graft substitutes, owing to their chemical similarities to the mineral part of bone matrix and off-the-shelf availability. However, their ability to regenerate bone in critical-sized bone defects has remained inferior to the gold standard autologous bone. Hence, there is a need for methods that can be employed to efficiently produce CaPs with different properties, enabling the screening and consequent fine-tuning of the properties of CaPs towards effective bone regeneration. To this end, we propose the use of droplet microfluidics for rapid production of a variety of CaP microparticles. Particularly, this study aims to optimize the steps of a droplet microfluidic-based production process, including droplet generation, in-droplet CaP synthesis, purification and sintering, in order to obtain a library of CaP microparticles with fine-tuned properties. The results showed that size-controlled, monodisperse water-in-oil microdroplets containing calcium- and phosphate-rich solutions can be produced using a flow-focusing droplet-generator microfluidic chip. We optimized synthesis protocols based on in-droplet mineralization to obtain a range of CaP microparticles without and with inorganic additives. This was achieved by adjusting synthesis parameters, such as precursor concentration, pH value, and aging time, and applying heat treatment. In addition, our results indicated that the synthesis and fabrication parameters of CaPs in this method can alter the microstructure and the degradation behavior of CaPs. Overall, the results highlight the potential of the droplet microfluidic platform for engineering CaP microparticle biomaterials with fine-tuned properties.

AI-enabled organoids: Construction, analysis, and application

Organoids, miniature and simplified in vitro model systems that mimic the structure and function of organs, have attracted considerable interest due to their promising applications in disease modeling, drug screening, personalized medicine, and tissue engineering. Despite the substantial success in cultivating physiologically relevant organoids, challenges remain concerning the complexities of their assembly and the difficulties associated with data analysis. The advent of AI-Enabled Organoids, which interfaces with artificial intelligence (AI), holds the potential to revolutionize the field by offering novel insights and methodologies that can expedite the development and clinical application of organoids. This review succinctly delineates the fundamental concepts and mechanisms underlying AI-Enabled Organoids, summarizing the prospective applications on rapid screening of construction strategies, cost-effective extraction of multiscale image features, streamlined analysis of multi-omics data, and precise preclinical evaluation and application. We also explore the challenges and limitations of interfacing organoids with AI, and discuss the future direction of the field. Taken together, the AI-Enabled Organoids hold significant promise for advancing our understanding of organ development and disease progression, ultimately laying the groundwork for clinical application.

A paradigm for high-throughput screening of cell-selective surfaces coupling orthogonal gradients and machine learning-based cell recognition

The combinational density of immobilized functional molecules on biomaterial surfaces directs cell behaviors. However, limited by the low efficiency of traditional low-throughput experimental methods, investigation and optimization of the combinational density remain daunting challenges. Herein, we report a high-throughput screening set-up to study biomaterial surface functionalization by integrating photo-controlled thiol-ene surface chemistry and machine learning-based label-free cell identification and statistics. Through such a strategy, a specific surface combinational density of polyethylene glycol (PEG) and arginine-glutamic acid-aspartic acid-valine peptide (REDV) leads to high endothelial cell (EC) selectivity against smooth muscle cell (SMC) was identified. The composition was translated as a coating formula to modify medical nickel-titanium alloy surfaces, which was then proved to improve EC competitiveness and induce endothelialization. This work provided a high-throughput method to investigate behaviors of co-cultured cells on biomaterial surfaces modified with combinatorial functional molecules.

Introduction of Materials Genome Technology and Its Applications in the Field of Biomedical Materials

Traditional research and development (R&D) on biomedical materials depends heavily on the trial and error process, thereby leading to huge economic and time burden. Most recently, materials genome technology (MGT) has been recognized as an effective approach to addressing this problem. In this paper, the basic concepts involved in the MGT are introduced, and the applications of MGT in the R&D of metallic, inorganic non-metallic, polymeric, and composite biomedical materials are summarized; in view of the existing limitations of MGT for R&D of biomedical materials, potential strategies are proposed on the establishment and management of material databases, the upgrading of high-throughput experimental technology, the construction of data mining prediction platforms, and the training of relevant materials talents. In the end, future trend of MGT for R&D of biomedical materials is proposed.

Design and Manufacture of a Low-Cost Microfluidic System for the Synthesis of Giant Liposomes for the Encapsulation of Yeast Homologues: Applications in the Screening of Membrane-Active Peptide Libraries

The discovery of new membrane-active peptides (MAPs) is an area of considerable interest in modern biotechnology considering their ample applicability in several fields ranging from the development of novel delivery vehicles (via cell-penetrating peptides) to responding to the latent threat of antibiotic resistance (via antimicrobial peptides). Different strategies have been devised for such discovery process, however, most of them involve costly, tedious, and low-efficiency methods. We have recently proposed an alternative route based on constructing a non-rationally designed library recombinantly expressed on the yeasts’ surfaces. However, a major challenge is to conduct a robust and high-throughput screening of possible candidates with membrane activity. Here, we addressed this issue by putting forward low-cost microfluidic platforms for both the synthesis of Giant Unilamellar Vesicles (GUVs) as mimicking entities of cell membranes and for providing intimate contact between GUVs and homologues of yeasts expressing MAPs. The homologues were chitosan microparticles functionalized with the membrane translocating peptide Buforin II, while intimate contact was through passive micromixers with different channel geometries. Both microfluidic platforms were evaluated both in silico (via Multiphysics simulations) and in vitro with a high agreement between the two approaches. Large and stable GUVs (5–100 µm) were synthesized effectively, and the mixing processes were comprehensively studied leading to finding the best operating parameters. A serpentine micromixer equipped with circular features showed the highest average encapsulation efficiencies, which was explained by the unique mixing patterns achieved within the device. The microfluidic devices developed here demonstrate high potential as platforms for the discovery of novel MAPs as well as for other applications in the biomedical field such as the encapsulation and controlled delivery of bioactive compounds.

Preparation of a modified g-C3N4 catalyst library and realization of a two-dimensional screening reaction

A color inkjet printing technique and high through-put screening technique were combined to establish a polymetallic sulphide composite g-C₃N₄ catalyst library and screen out high efficiency catalysts.

Microfluidic High-Throughput Platforms for Discovery of Novel Materials

High-throughput screening is a potent technique to accelerate the discovery and development of new materials. By performing massive synthesis and characterization processes in parallel, it can rapidly discover materials with desired components, structures and functions. Among the various approaches for high-throughput screening, microfluidic platforms have attracted increasing attention. Compared with many current strategies that are generally based on robotic dispensers and automatic microplates, microfluidic platforms can significantly increase the throughput and reduce the consumption of reagents by several orders of magnitude. In this review, we first introduce current advances of the two types of microfluidic high-throughput platforms based on microarrays and microdroplets, respectively. Then the utilization of these platforms for screening different types of materials, including inorganic metals, metal alloys and organic polymers are described in detail. Finally, the challenges and opportunities in this promising field are critically discussed.

Design, Screening, and Testing of Non-Rational Peptide Libraries with Antimicrobial Activity: In Silico and Experimental Approaches

One of the challenges of modern biotechnology is to find new routes to mitigate the resistance to conventional antibiotics. Antimicrobial peptides (AMPs) are an alternative type of biomolecules, naturally present in a wide variety of organisms, with the capacity to overcome the current microorganism resistance threat. Here, we reviewed our recent efforts to develop a new library of non-rationally produced AMPs that relies on bacterial genome inherent diversity and compared it with rationally designed libraries. Our approach is based on a four-stage workflow process that incorporates the interplay of recent developments in four major emerging technologies: artificial intelligence, molecular dynamics, surface-display in microorganisms, and microfluidics. Implementing this framework is challenging because to obtain reliable results, the in silico algorithms to search for candidate AMPs need to overcome issues of the state-of-the-art approaches that limit the possibilities for multi-space data distribution analyses in extremely large databases. We expect to tackle this challenge by using a recently developed classification algorithm based on deep learning models that rely on convolutional layers and gated recurrent units. This will be complemented by carefully tailored molecular dynamics simulations to elucidate specific interactions with lipid bilayers. Candidate AMPs will be recombinantly-expressed on the surface of microorganisms for further screening via different droplet-based microfluidic-based strategies to identify AMPs with the desired lytic abilities. We believe that the proposed approach opens opportunities for searching and screening bioactive peptides for other applications.

A Microarray Screening Platform with an Experimental Conditions Gradient Generator for the High-Throughput Synthesis of Micro/Nanosized Calcium Phosphates

Calcium phosphates (CaP) represent an impressive kind of biomedical material due to their excellent biocompatibility, bioactivity, and biodegradability. Their morphology and structure highly influence their properties and applications. Whilst great progress has been made in research on biomedical materials, there is still a need to develop a method that can rapidly synthesize and screen micro/nanosized biomedical materials. Here, we utilized a microarray screening platform that could provide the high-throughput synthesis of biomedical materials and screen the vital reaction conditions. With this screening platform, 9 × 9 sets of parallel experiments could be conducted simultaneously with one- or two-dimensions of key reaction condition gradients. We used this platform to establish a one-dimensional gradient of the pH and citrate concentration and a two-dimensional gradient of both the Ca/P ratio and pH to synthesize CaP particles with various morphologies. This screening platform also shows the potential to be extended to other reaction systems for rapid high-throughput screening.