**1. Introduction**

Stem cells can differentiate into specific cell subtypes, which has resulted in the development of tissue engineering and regenerative medicine [1,2]. Due to stem cells' ability to produce cells in vitro that are associated with the physiological functions of specific tissues, stem cell therapy has emerged as a potential solution for many diseases that are difficult to treat with conventional chemotherapy over the past few decades [3–6]. There have been 40,183 research papers about stem cell therapy published between 1971 and 2021; many of these studies demonstrated its clinical potential. However, the only stem cell therapy approved by the United States Food and Drug Administration to date is haematopoietic (or blood) stem cell transplantation [7–10].

There are many challenges in the development of stem cell therapy, including low differentiation efficiency, differentiation into undesired cell subtypes, carcinogenesis, and post-transplant inflammatory response [11,12]. Therefore, many stem cell differentiation studies have been conducted to (i) understand the developmental stages of stem cell differentiation, (ii) control stem cell behaviour in vitro, and (iii) enhance stem cell differentiation efficiency [13–16]. Consequently, a need for measuring stem cell differentiation using a variety of analytical methods has arisen. These techniques include polymerase chain reaction (PCR), immunocytochemistry, flow cytometry and Western blot (WB), which have been widely used with biomarkers, such as proteins, ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) [17–20]. However, these techniques are destructive, laborious, and costly; therefore, they are inappropriate for the quantitative and qualitative analysis of differentiated cells prearranged in therapeutic transplantation [21]. Hence, nondestructive and real-time monitoring of cell differentiation is necessary for efficient stem cell therapy. Many biosensing and nanotechnology methods have been proposed for the

**Citation:** Kang, M.-J.; Cho, Y.-W.; Kim, T.-H. Progress in Nano-Biosensors for Non-Invasive Monitoring of Stem Cell Differentiation. *Biosensors* **2023**, *13*, 501. https://doi.org/10.3390/ bios13050501

Received: 23 February 2023 Revised: 20 April 2023 Accepted: 22 April 2023 Published: 26 April 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

non-invasive monitoring of stem cell differentiation, such as impedance and Raman spectroscopy, deep learning-based approaches, electrochemical immunoassay biosensors, and electroluminescence [22–33]. In particular, electrochemistry-based sensing methods, such as impedance spectroscopy and electroluminescence, have been demonstrated as analytical techniques that selectively detect target materials through electrical signals generated from the redox reaction of analytes. These techniques have the following advantages: (i) facile, (ii) inexpensive, (iii) simple, portable analytical devices, and (iv) non-invasive [34–38]. Similarly, optical sensing methods, such as fluorescence, near-infrared (NIR), and Raman spectroscopy, can selectively detect the optical properties or signals of target materials. These methods have the following advantageous features: (i) high selectivity, (ii) flexibility, and (iii) non-invasive [39–44].

The medium for in vitro stem cell cultivation contains cells with many organelles, but also several types of proteins, small molecules, and other chemicals; this means that the analytical conditions for cell-based sensing are highly complex [41,45]. Therefore, improving sensing performance, including sensitivity and selectivity towards target analytes, is essential for the accurate and sensitive label-free monitoring of stem cell differentiation with electrochemical or optical-based sensors. More specifically, a highly sensitive sensing capability for differentiation-associated targets is required to quantitatively analyse how much differentiation was induced from the stem cells in real-time. In addition, to qualitatively analyse whether specific differentiation into desired cell subtypes has been induced during stem cell differentiation, selectivity for the analytes is a key indicator.

Various nano- and micromaterials have been used to modify sensor surfaces to improve performance, including sensitivity, selectivity, and reliability [44,46]. For instance, highly conductive metal nanomaterials, such as gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs), and carbon-based conductive materials, such as graphene oxide (GO), have excellent electrical or electrochemical properties and are widely used in electrochemical sensors [47,48]. In addition, three-dimensional (3D) micromaterials, such as microelectrode assays and microfluidics, have been used to improve electrochemical sensors' performance by increasing the active surface area [49–51]. In the case of Raman spectroscopy-based sensors, two-dimensional (2D) or 3D combinations of metal nanoparticles with good optical properties and carbon-based conductive materials have been used to improve the sensitivity [52,53]. However, each electrochemical and optical-based sensor's sensing mechanism is different; therefore, the strategies for improving the sensing performance and capabilities and the techniques for sensor surface modification are different.

This review highlights and compares recent studies on non-invasive and real-time monitoring of stem cell differentiation, including neurogenesis, cardiomyogenesis, osteogenesis, and adipogenesis (Figure 1). In addition, various biosensors fused with specific analysis technology, such as electrochemistry and optical sensing, and various nano- and micro materials, such as AuNPs, AgNPs, upconversion nanoparticles (UCNPs), autofluorescence probes, nucleic acids, microfluidic systems, and microelectrode arrays, are reviewed and compared (Table 1).

**Figure 1.** Schematic illustration of traditional sensing and nano- and micromaterial-based methods for monitoring stem cell differentiation. Created with BioRender.com.
