Cell viability prediction and optimization in extrusion-based bioprinting via neural network-based Bayesian optimization models.

The fields of regenerative medicine and cancer modeling have witnessed tremendous growth in the application of 3D bioprinting. Maintaining high cell viability throughout the bioprinting process is crucial for the success of this technology, as it directly affects the accuracy of the 3D bioprinted models, the validity of experimental results, and the discovery of new therapeutic approaches. Therefore, optimizing bioprinting conditions, which include numerous variables influencing cell viability during and after the procedure, is of utmost importance to achieve desirable results. So far, these optimizations have been accomplished primarily through trial and error and repeating multiple time-consuming and costly experiments. To address this challenge, we initiated the process by creating a dataset of these parameters for gelatin and alginate-based bioinks and the corresponding cell viability by integrating data obtained in our laboratory and those derived from the literature. Then, we developed machine learning models to predict cell viability based on different bioprinting variables. The trained neural network yielded regressionR2value of 0.71 and classification accuracy of 0.86. Compared to models that have been developed so far, the performance of our models is superior and shows great prediction results. The study further introduces a novel optimization strategy that employs the Bayesian optimization model in combination with the developed regression neural network to determine the optimal combination of the selected bioprinting parameters to maximize cell viability and eliminate trial-and-error experiments. Finally, we experimentally validated the optimization model's performance.

Controlled tumor heterogeneity in a co-culture system by 3D bio-printed tumor-on-chip model.

Cancer treatment resistance is a caused by presence of various types of cells and heterogeneity within the tumor. Tumor cell-cell and cell-microenvironment interactions play a significant role in the tumor progression and invasion, which have important implications for diagnosis, and resistance to chemotherapy. In this study, we develop 3D bioprinted in vitro models of the breast cancer tumor microenvironment made of co-cultured cells distributed in a hydrogel matrix with controlled architecture to model tumor heterogeneity. We hypothesize that the tumor could be represented by a cancer cell-laden co-culture hydrogel construct, whereas its microenvironment can be modeled in a microfluidic chip capable of producing a chemical gradient. Breast cancer cells (MCF7 and MDA-MB-231) and non-tumorigenic mammary epithelial cells (MCF10A) were embedded in the alginate-gelatine hydrogels and printed using a multi-cartridge extrusion bioprinter. Our approach allows for precise control over position and arrangements of cells in a co-culture system, enabling the design of various tumor architectures. We created samples with two different types of cells at specific initial locations, where the density of each cell type was carefully controlled. The cells were either randomly mixed or positioned in sequential layers to create cellular heterogeneity. To study cell migration toward chemoattractant, we developed a chemical microenvironment in a chamber with a gradual chemical gradient. As a proof of concept, we studied different migration patterns of MDA-MB-231 cells toward the epithelial growth factor gradient in presence of MCF10A cells in different ratios using this device. Our approach involves the integration of 3D bioprinting and microfluidic devices to create diverse tumor architectures that are representative of those found in various patients. This provides an excellent tool for studying the behavior of cancer cells with high spatial and temporal resolution.

Predicting and elucidating the post-printing behavior of 3D printed cancer cells in hydrogel structures by integrating in-vitro and in-silico experiments.

A key feature distinguishing 3D bioprinting from other 3D cell culture techniques is its precise control over created structures. This property allows for the high-resolution fabrication of biomimetic structures with controlled structural and mechanical properties such as porosity, permeability, and stiffness. However, analyzing post-printing cellular dynamics and optimizing their functions within the 3D fabricated environment is only possible through trial and error and replicating several experiments. This issue motivated the development of a cellular automata model for the first time to simulate post-printing cell behaviour within the 3D bioprinted construct. To improve our model, we bioprinted a 3D construct using MDA-MB-231 cell-laden hydrogel and evaluated cellular functions, including viability and proliferation in 11 days. The results showed that our model successfully simulated the 3D bioprinted structure and captured in-vitro observations. We demonstrated that in-silico model could predict and elucidate post-printing biological functions for different initial cell numbers in bioink and different bioink formulations with gelatine and alginate, without replicating several costly and time-consuming in-vitro measurements. We believe such a computational framework will substantially impact 3D bioprinting's future application. We hope this study inspires researchers to further realize how an in-silico model might be utilized to advance in-vitro 3D bioprinting research.

A Conductive Hydrogel-Based Microneedle Platform for Real-Time pH Measurement in Live Animals.

Conventional microneedles (MNs) have been extensively reported and applied toward a variety of biosensing and drug delivery applications. Hydrogel forming MNs with the added ability to electrically track health conditions in real-time is an area yet to be explored. The first conductive hydrogel microneedle (HMN) electrode that is capable of on-needle pH detection with no postprocessing required is presented here. The HMN array is fabricated using a swellable dopamine (DA) conjugated hyaluronic acid (HA) hydrogel, and is embedded with poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) to increase conductivity. The catechol-quinone chemistry intrinsic to DA is used to measure pH in interstitial fluid (ISF). The effect of PEDOT:PSS on the characteristics of the HMN array such as swelling capability and mechanical strength is fully studied. The HMN's capability for pH measurement is first demonstrated using porcine skin equilibrated with different pH solutions ranging from 3.5 to 9. Furthermore, the HMN-pH meter is capable of in vivo measurements with a 93% accuracy compared to a conventional pH probe meter. This HMN technology bridges the gap between traditional metallic electrochemical biosensors and the direct extraction of ISF, and introduces a platform for the development of polymeric wearable sensors capable of on-needle detection.

Egg shell-derived calcium phosphate/carbon dot nanofibrous scaffolds for bone tissue engineering: Fabrication and characterization.

Recent exciting findings of the particular properties of Carbon dot (CDs) have shed light on potential biomedical applications of CDs-containing composites. While CDs so far have been widely used as biosensors and bioimaging agents, in the present study for the first time, we evaluate the osteoconductivity of CDs in poly (ε-caprolactone) (PCL)/polyvinyl alcohol (PVA) [PCL/PVA] nanofibrous scaffolds. Moreover, further studies were performed to evaluate egg shell-derived calcium phosphate (TCP3) and its cellular responses, biocompatibility and in vitro osteogenesis. Scaffolds were fabricated by simultaneous electrospinning of PCL with three different types of calcium phosphate, PVA and CDs. Fabricated scaffolds were characterized by Scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), contact angle measurement and degradation assessment. SEM, the methyl thiazolyl tetrazolium (MTT) assay, and alkaline phosphatase (ALP) activity test were performed to evaluate cell morphology, proliferation and osteogenic differentiation, respectively. The results demonstrated that while the addition of just 1 wt% CDs and TCP3 individually into PCL/PVA nanocomposite enhanced ALP activity and cell proliferation rate (p < 0.05), the synergetic effect of CDs/TCP3 led to highest osteogenic differentiation and proliferation rate compared to other scaffolds (p < 0.05). Hence, CDs and PCL/PVA-TCP3 could serve as a potential candidate for bone tissue regeneration.

In vitro effect of graphene structures as an osteoinductive factor in bone tissue engineering: A systematic review.

Graphene and its derivatives have been well-known as influential factors in differentiating stem/progenitor cells toward the osteoblastic lineage. However, there have been many controversies in the literature regarding the parameters effect on bone regeneration, including graphene concentration, size, type, dimension, hydrophilicity, functionalization, and composition. This study attempts to produce a comprehensive review regarding the given parameters and their effects on stimulating cell behaviors such as proliferation, viability, attachment and osteogenic differentiation. In this study, a systematic search of MEDLINE database was conducted for in vitro studies on the use of graphene and its derivatives for bone tissue engineering from January 2000 to February 2018, organized according to the PRISMA statement. According to reviewed articles, different graphene derivative, including graphene, graphene oxide (GO) and reduced graphene oxide (RGO) with mass ratio ≤1.5 wt % for all and concentration up to 50 µg/mL for graphene and GO, and 60 µg/mL for RGO, are considered to be safe for most cell types. However, these concentrations highly depend on the types of cells. It was discovered that graphene with lateral size less than 5 µm, along with GO and RGO with lateral dimension less than 1 µm decrease cell viability. In addition, the three-dimensional structure of graphene can promote cell-cell interaction, migration and proliferation. When graphene and its derivatives are incorporated with metals, polymers, and minerals, they frequently show promoted mechanical properties and bioactivity. Last, graphene and its derivatives have been found to increase the surface roughness and porosity, which can highly enhance cell adhesion and differentiation. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 2284-2343, 2018.