Toilet-based continuous health monitoring using urine

Sample preparation and detection methods in point-of-care devices towards future at-home testing

Timely and accurate diagnosis is critical for effective healthcare, yet nearly half the global population lacks access to basic diagnostics. Point-of-care (POC) testing offers partial solutions by enabling low-cost, rapid diagnosis at the patient's location. At-home POC devices have the potential to advance preventive care and early disease detection. Nevertheless, effective sample preparation and detection methods are essential for accurate results. This review surveys recent advances in sample preparation and detection methods at POC. The goal is to provide an in-depth understanding of how these technologies can enhance at-home POC devices. Lateral flow assays, nucleic acid tests, and virus detection methods are at the forefront of POC diagnostic technology, offering rapid and sensitive tools for identifying and measuring pathogens, biomarkers, and viral infections. By illuminating cutting-edge research on assay development for POC diagnostics, this review aims to accelerate progress towards widely available, user-friendly, at-home health monitoring tools that empower individuals in personalized healthcare in the future.

Repurposing Sewage and Toilet Systems: Environmental, Public Health, and Person-Centered Healthcare Applications

Global terrestrial water supplies are rapidly depleting due to the consequences of climate change. Water scarcity results in an inevitable compromise of safe hygiene and sanitation practices, leading to the transmission of water-borne infectious diseases, and the preventable deaths of over 800.000 people each year. Moreover, almost 500 million people lack access to toilets and sanitation systems. Ecosystems are estimated to be contaminated by 6.2 million tons of nitrogenous products from human wastewater management practices. It is therefore imperative to transform toilet and sewage systems to promote equitable access to water and sanitation, improve public health, conserve water, and protect ecosystems. Here, the integration of emerging technologies in toilet and sewage networks to repurpose toilet and wastewater systems is reviewed. Potential applications of these systems to develop sustainable solutions to environmental challenges, promote public health, and advance person-centered healthcare are discussed.

AI-Based Metamaterial Design

The use of metamaterials in various devices has revolutionized applications in optics, healthcare, acoustics, and power systems. Advancements in these fields demand novel or superior metamaterials that can demonstrate targeted control of electromagnetic, mechanical, and thermal properties of matter. Traditional design systems and methods often require manual manipulations which is time-consuming and resource intensive. The integration of artificial intelligence (AI) in optimizing metamaterial design can be employed to explore variant disciplines and address bottlenecks in design. AI-based metamaterial design can also enable the development of novel metamaterials by optimizing design parameters that cannot be achieved using traditional methods. The application of AI can be leveraged to accelerate the analysis of vast data sets as well as to better utilize limited data sets via generative models. This review covers the transformative impact of AI and AI-based metamaterial design for optics, acoustics, healthcare, and power systems. The current challenges, emerging fields, future directions, and bottlenecks within each domain are discussed.

Porous Microneedles Through Direct Ink Drawing with Nanocomposite Inks for Transdermal Collection of Interstitial Fluid

Interstitial fluid (ISF) is an attractive alternative to regular blood sampling for health checks and disease diagnosis. Porous microneedles (MNs) are well suited for collecting ISF in a minimally invasive manner. However, traditional methods of molding MNs from microfabricated templates involve prohibitive fabrication costs and fixed designs. To overcome these limitations, this study presents a facile and economical additive manufacturing approach to create porous MNs. Compared to traditional layerwise build sequences, direct ink drawing with nanocomposite inks can define sharp MNs with tailored shapes and achieve vastly improved fabrication efficiency. The key to this fabrication strategy is the yield-stress fluid ink that is easily formulated by dispersing silica nanoparticles into the cellulose acetate polymer solution. As-printed MNs are solidified into interconnected porous microstructure inside a coagulation bath of deionized water. The resulting MNs exhibit high mechanical strength and high porosity. This approach also allows porous MNs to be easily integrated on various substrates. In particular, MNs on filter paper substrates are highly flexible to rapidly collect ISF on non-flat skin sites. The extracted ISF is used for quantitative analysis of biomarkers, including glucose, = calcium ions, and calcium ions. Overall, the developments allow facile fabrication of porous MNs for transdermal diagnosis and therapy.

Deep learning-augmented T-junction droplet generation

Droplet generation technology has become increasingly important in a wide range of applications, including biotechnology and chemical synthesis. T-junction channels are commonly used for droplet generation due to their integration capability of a larger number of droplet generators in a compact space. In this study, a finite element analysis (FEA) approach is employed to simulate droplet production and its dynamic regimes in a T-junction configuration and collect data for post-processing analysis. Next, image analysis was performed to calculate the droplet length and determine the droplet generation regime. Furthermore, machine learning (ML) and deep learning (DL) algorithms were applied to estimate outputs through examination of input parameters within the simulation range. At the end, a graphical user interface (GUI) was developed for estimation of the droplet characteristics based on inputs, enabling the users to preselect their designs with comparable microfluidic configurations within the studied range.

The transition from genomics to phenomics in personalized population health

Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.

Fully Transient 3D Origami Paper-Based Ammonia Gas Sensor Obtained by Facile MXene Spray Coating

Developing high-performance chemiresistive gas sensors with mechanical compliance for environmental or health-related biomarker monitoring has recently drawn increasing research attention. Among them, two-dimensional MXene materials hold great potential for room-temperature hazardous gas (e.g., NH3) monitoring regardless of the complicated fabrication process, insufficient 2D/3D flexibilities, and poor environmental sustainability. Herein, a Ti3C2Tx MXene/gelatin ink was developed for patterning electrodes through a facile spray coating. Particularly, the patterned Ti3C2Tx-based coating exhibited good adhesion on the paper substrate against repeated peeling-off and excellent mechanical flexibility against 1000 cyclic stretching. The porous morphology of the coating facilitated the NH3 sensing ability. As a result, the 2D kirigami-shaped NH3 sensor exhibited a good response of 7% to 50 ppm of NH3 with detectable concentrations ranging from 5-500 ppm, decent selectivity over interferences, etc., which could be well-maintained even at 50% stretched state. In addition, with the help of mechanically guided compressive buckling, 3D mesostructured MXene origamis could be obtained, holding promise for detecting the coming direction and height distribution of hazardous gas, e.g., the NH3. More importantly, the as-fabricated MXene/gelatin origami paper could be fully degraded in PBS/H2O2/cellulase solution within 19 days, demonstrating its potential as a high-performance, shape morphable, and environmentally friendly wearable gas sensor.

How the adaptation of the human microbiome to harsh space environment can determine the chances of success for a space mission to Mars and beyond

The ability of human cells to adapt to space radiation is essential for the well-being of astronauts during long-distance space expeditions, such as voyages to Mars or other deep space destinations. However, the adaptation of the microbiomes should not be overlooked. Microorganisms inside an astronaut's body, or inside the space station or other spacecraft, will also be exposed to radiation, which may induce resistance to antibiotics, UV, heat, desiccation, and other life-threatening factors. Therefore, it is essential to consider the potential effects of radiation not only on humans but also on their microbiomes to develop effective risk reduction strategies for space missions. Studying the human microbiome in space missions can have several potential benefits, including but not limited to a better understanding of the major effects space travel has on human health, developing new technologies for monitoring health and developing new radiation therapies and treatments. While radioadaptive response in astronauts' cells can lead to resistance against high levels of space radiation, radioadaptive response in their microbiome can lead to resistance against UV, heat, desiccation, antibiotics, and radiation. As astronauts and their microbiomes compete to adapt to the space environment. The microorganisms may emerge as the winners, leading to life-threatening situations due to lethal infections. Therefore, understanding the magnitude of the adaptation of microorganisms before launching a space mission is crucial to be able to develop effective strategies to mitigate the risks associated with radiation exposure. Ensuring the safety and well-being of astronauts during long-duration space missions and minimizing the risks linked with radiation exposure can be achieved by adopting this approach.

Anesthesia Patient Monitoring 2050

The monitoring of vital signs in patients undergoing anesthesia began with the very first case of anesthesia and has evolved alongside the development of anesthesiology ever since. Patient monitoring started out as a manually performed, intermittent, and qualitative assessment of the patient's general well-being in the operating room. In its evolution, patient monitoring development has responded to the clinical need, for example, when critical incident studies in the 1980s found that many anesthesia adverse events could be prevented by improved monitoring, especially respiratory monitoring. It also facilitated and perhaps even enabled increasingly complex surgeries in increasingly higher-risk patients. For example, it would be very challenging to perform and provide anesthesia care during some of the very complex cardiovascular surgeries that are almost routine today without being able to simultaneously and reliably monitor multiple pressures in a variety of places in the circulatory system. Of course, anesthesia patient monitoring itself is enabled by technological developments in the world outside of the operating room. Throughout its history, anesthesia patient monitoring has taken advantage of advancements in material science (when nonthrombogenic polymers allowed the design of intravascular catheters, for example), in electronics and transducers, in computers, in displays, in information technology, and so forth. Slower product life cycles in medical devices mean that by carefully observing technologies such as consumer electronics, including user interfaces, it is possible to peek ahead and estimate with confidence the foundational technologies that will be used by patient monitors in the near future. Just as the discipline of anesthesiology has, the patient monitoring that accompanies it has come a long way from its beginnings in the mid-19th century. Extrapolating from careful observations of the prevailing trends that have shaped anesthesia patient monitoring historically, patient monitoring in the future will use noncontact technologies, will predict the trajectory of a patient's vital signs, will add regional vital signs to the current systemic ones, and will facilitate directed and supervised anesthesia care over the broader scope that anesthesia will be responsible for.

Wearable and Implantable Cortisol-Sensing Electronics for Stress Monitoring

Cortisol is a steroid hormone that is released from the body in response to stress. Although a moderate level of cortisol secretion can help the body maintain homeostasis, excessive secretion can cause various diseases, such as depression and anxiety. Conventional methods for cortisol measurement undergo procedures that limit continuous monitoring, typically collecting samples of bodily fluids, followed by separate analysis in a laboratory setting that takes several hours. Thus, recent studies demonstrate wearable, miniaturized sensors integrated with electronic modules that enable wireless real-time analysis. Here, the primary focus is on wearable and implantable electronic devices that continuously measure cortisol concentration. Diverse types of cortisol-sensing techniques, such as antibody-, DNA-aptamer-, and molecularly imprinted polymer-based sensors, as well as wearable and implantable devices that aim to continuously monitor cortisol in a minimally invasive fashion are discussed. In addition to the cortisol monitors that directly measure stress levels, other schemes that indirectly measure stress, such as electrophysiological signals and sweat are also summarized. Finally, the challenges and future directions in stress monitoring and management electronics are reviewed.

Technological Innovations to Improve Patient Engagement in Nephrology

Technological innovation has accelerated exponentially over the last 2 decades. From the rise of smartphones and social media in the early 2000s to the mainstream accessibility of artificial intelligence (AI) in 2023, digital advancements have transformed the way we live and work. These innovations have permeated health care, covering a spectrum of applications from virtual reality training platforms to AI-powered clinical decision support tools. In this review, we explore fascinating recent innovations that have and can facilitate patient engagement in nephrology. These include integrated care mobile applications, wearable health monitoring tools, virtual/augmented reality consultation and education platforms, AI-powered appointment booking systems, and patient information tools. We also discuss potential pitfalls in implementation and paradigms to adopt that may protect patients from unintended consequences of being cared for in a digitalized health care system.

Older Adults' Perceptions About Using Intelligent Toilet Seats Beyond Traditional Care: Web-Based Interview Survey

BACKGROUND

In contemporary society, age tech (age technology) represents a significant advancement in health care aimed at enhancing patient engagement, ensuring sustained independence, and promoting quality of life for older people. One innovative form of age tech is the intelligent toilet seat, which is designed to collect, analyze, and provide insights based on toileting logs and excreta data. Understanding how older people perceive and interact with such technology can offer invaluable insights to researchers, technology developers, and vendors.

OBJECTIVE

This study examined older adults' perspectives regarding the use of intelligent toilet seats. Through a qualitative methodology, this research aims to unearth the nuances of older people's opinions, shedding light on their preferences, concerns, and potential barriers to adoption.

METHODS

Data were collected using a web-based interview survey distributed on Amazon Mechanical Turk. The analyzed data set comprised 174 US-based individuals aged ≥65 years who voluntarily participated in this study. The qualitative data were carefully analyzed using NVivo (Lumivero) based on detailed content analysis, ensuring that emerging themes were coded and classified based on the conceptual similarities in the respondents' narratives.

RESULTS

The analysis revealed 5 dominant themes encompassing the opinions of aging adults. The perceived benefits and advantages of using the intelligent toilet seat were grouped into 3 primary themes: health-related benefits including the potential for early disease detection, continuous health monitoring, and seamless connection to health care insights. Technology-related advantages include the noninvasive nature of smart toilet seats and leveraging unique and innovative data collection and analysis technology. Use-related benefits include ease of use, potential for multiple users, and cost reduction owing to the reduced need for frequent clinical visits. Conversely, the concerns and perceived risks were classified into 2 significant themes: psychological concerns, which included concerns about embarrassment and aging-related stereotypes, and the potential emotional impact of constant health monitoring. Technical performance risks include concerns centered on privacy and security, device reliability, data accuracy, potential malfunctions, and the implications of false positives or negatives.

CONCLUSIONS

The decision of older adults to incorporate intelligent toilet seats into their daily lives depends on myriad factors. Although the potential health and technological benefits are evident, valid concerns that need to be addressed remain. To foster widespread adoption, it is imperative to enhance the advantages while simultaneously addressing and mitigating the identified risks. This balanced approach will pave the way for a more holistic integration of smart health care devices into the routines of the older population, ensuring that they reap the full benefits of age tech advancements.

Biosensors for prostate cancer detection

Prostate cancer (PC) is one of the most common tumors and a leading cause of mortality among men, resulting in ~375 000 deaths annually worldwide. Various analytical methods have been designed for quantitative and rapid detection of PC biomarkers. Electrochemical (EC), optical, and magnetic biosensors have been developed to detect tumor biomarkers in clinical and point-of-care (POC) settings. Although POC biosensors have shown potential for detection of PC biomarkers, some limitations, such as the sample preparation, should be considered. To tackle such shortcomings, new technologies have been utilized for development of more practical biosensors. Here, biosensing platforms for the detection of PC biomarkers such as immunosensors, aptasensors, genosensors, paper-based devices, microfluidic systems, and multiplex high-throughput platforms, are discussed.

Highly Sensitive Detection of Formaldehyde by Laser-Induced Graphene-Coated Silver Nanoparticles Electrochemical Sensing Electrodes

Formaldehyde (HCHO) poses a grave threat to human health because of its toxicity, but its accurate, sensitive, and rapid detection in aqueous solutions remains a major challenge. This study proposes a novel electrochemical sensor composed of a graphene-based electrode that is prepared via laser induction technology. The precursor material, polyimide, is modified via the metal ion exchange method, and the detective electrode is coated with graphene and silver nanoparticles. And the special structure of graphene-coated Ag was demonstrated using scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM), and X-ray diffraction (XRD), Fourier transform infrared (FT-IR), and X-ray photoelectron spectroscopy (XPS) results show that graphene provides more sites for Ag NRs to be exposed and increases the surface area of contact between the solution and the detection object. In addition, differential pulse voltammetry (DPV) analysis exhibits high linearity over the HCHO concentration range from 0.05 to 5 μg/mL, with a detection limit of 0.011 μg/mL (S/N = 3). The Ag NPs in the electrochemical reaction will adsorb the intermediate •CO and •OH, catalyze their combination, and finally convert to CO2 and H2O, respectively. A microdetection device, specially designed for use with commercial micro-workstations, is employed to fully demonstrate the practical application of the electrode, which paves a way for developing formaldehyde electrochemical sensors.

3D-Printed Microrobots: Translational Challenges

The science of microrobots is accelerating towards the creation of new functionalities for biomedical applications such as targeted delivery of agents, surgical procedures, tracking and imaging, and sensing. Using magnetic properties to control the motion of microrobots for these applications is emerging. Here, 3D printing methods are introduced for the fabrication of microrobots and their future perspectives are discussed to elucidate the path for enabling their clinical translation.

The Metaverse for Healthcare: Trends, Applications, and Future Directions of Digital Therapeutics for Urology

In recent years, the emergence of digital therapeutics as a novel approach to managing conditions has garnered significant attention. This approach involves using evidence-based therapeutic interventions that are facilitated by high-quality software programs to treat, manage, or prevent medical conditions. The incorporation of digital therapeutics into the Metaverse has increased the feasibility of their implementation and application in all areas of medical services. In urology, substantial digital therapeutics are being produced and researched, including mobile apps, bladder devices, pelvic floor muscle trainers, smart toilet systems, mixed reality-guided training and surgery, and training and telemedicine for urological consultations. The purpose of this review article is to provide a comprehensive overview of the current impact of the Metaverse on the field of digital therapeutics and identify its current trends, applications, and future perspectives in the field of urology.

Microneedle arrays integrated with microfluidic systems: Emerging applications and fluid flow modeling

Microneedle arrays are patches of needles at micro- and nano-scale, which are competent and versatile technologies that have been merged with microfluidic systems to construct more capable devices for biomedical applications, such as drug delivery, wound healing, biosensing, and sampling body fluids. In this paper, several designs and applications are reviewed. In addition, modeling approaches used in microneedle designs for fluid flow and mass transfer are discussed, and the challenges are highlighted.

Passive monitoring by smart toilets for precision health

Smart toilets are a key tool for enabling precision health monitoring in the home, but such passive monitoring has ethical considerations.

A Comprehensive Review of the Recent Developments in Wearable Sweat-Sensing Devices

Sweat analysis offers non-invasive real-time on-body measurement for wearable sensors. However, there are still gaps in current developed sweat-sensing devices (SSDs) regarding the concerns of mixing fresh and old sweat and real-time measurement, which are the requirements to ensure accurate the measurement of wearable devices. This review paper discusses these limitations by aiding model designs, features, performance, and the device operation for exploring the SSDs used in different sweat collection tools, focusing on continuous and non-continuous flow sweat analysis. In addition, the paper also comprehensively presents various sweat biomarkers that have been explored by earlier works in order to broaden the use of non-invasive sweat samples in healthcare and related applications. This work also discusses the target analyte's response mechanism for different sweat compositions, categories of sweat collection devices, and recent advances in SSDs regarding optimal design, functionality, and performance.

3D-printed microrobots from design to translation

Microrobots have attracted the attention of scientists owing to their unique features to accomplish tasks in hard-to-reach sites in the human body. Microrobots can be precisely actuated and maneuvered individually or in a swarm for cargo delivery, sampling, surgery, and imaging applications. In addition, microrobots have found applications in the environmental sector (e.g., water treatment). Besides, recent advancements of three-dimensional (3D) printers have enabled the high-resolution fabrication of microrobots with a faster design-production turnaround time for users with limited micromanufacturing skills. Here, the latest end applications of 3D printed microrobots are reviewed (ranging from environmental to biomedical applications) along with a brief discussion over the feasible actuation methods (e.g., on- and off-board), and practical 3D printing technologies for microrobot fabrication. In addition, as a future perspective, we discussed the potential advantages of integration of microrobots with smart materials, and conceivable benefits of implementation of artificial intelligence (AI), as well as physical intelligence (PI). Moreover, in order to facilitate bench-to-bedside translation of microrobots, current challenges impeding clinical translation of microrobots are elaborated, including entry obstacles (e.g., immune system attacks) and cumbersome standard test procedures to ensure biocompatibility.

Microbots have attracted attention due to an ability to reach places and perform tasks which are not possible with conventional techniques in a wide range of applications. Here, the authors review the recent work in the field on the fabrication, application and actuation of 3D printed microbots offering a view of the direction of future microbot research.

Disposable Paper-Based Microfluidics for Fertility Testing

Fifteen percent of couples of reproductive age suffer from infertility globally and the burden of infertility disproportionately impacts residents of developing countries. Assisted reproductive technologies (ARTs), including in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI), have been successful in overcoming various reasons for infertility including borderline and severe male factor infertility which consists of 20%–30% of all infertile cases. Approximately half of male infertility cases stem from suboptimal sperm parameters. Therefore, healthy/normal sperm enrichment and sorting remains crucial in advancing reproductive medicine. Microfluidic technologies have emerged as promising tools to develop in-home rapid fertility tests and point-of-care (POC) diagnostic tools. Here, we review advancements in fabrication methods for paper-based microfluidic devices and their emerging fertility testing applications assessing sperm concentration, sperm motility, sperm DNA analysis, and other sperm functionalities, and provide a glimpse into future directions for paper-based fertility microfluidic systems.

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Paper-based technologies are emerging to develop in-home rapid fertility tests

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Fabrication methods for paper-based microfluidic devices are presented

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Emerging disposable paper-based fertility testing applications are reviewed

3D-Printed Microneedles for Point-of-Care Biosensing Applications

Microneedles (MNs) are an emerging technology for user-friendly and minimally invasive injection, offering less pain and lower tissue damage in comparison to conventional needles. With their ability to extract body fluids, MNs are among the convenient candidates for developing biosensing setups, where target molecules/biomarkers are detected by the biosensor using the sample collected with the MNs. Herein, we discuss the 3D printing of microneedle arrays (MNAs) toward enabling point-of-care (POC) biosensing applications.

Microfluidic Invasion Chemotaxis Platform for 3D Neurovascular Co-Culture

Advances in microfabrication and biomaterials have enabled the development of microfluidic chips for studying tissue and organ models. While these platforms have been developed primarily for modeling human diseases, they are also used to uncover cellular and molecular mechanisms through in vitro studies, especially in the neurovascular system, where physiological mechanisms and three-dimensional (3D) architecture are difficult to reconstruct via conventional assays. An extracellular matrix (ECM) model with a stable structure possessing the ability to mimic the natural extracellular environment of the cell efficiently is useful for tissue engineering applications. Conventionally used techniques for this purpose, for example, Matrigels, have drawbacks of owning complex fabrication procedures, in some cases not efficient enough in terms of functionality and expenses. Here, we proposed a fabrication protocol for a GelMA hydrogel, which has shown structural stability and the ability to imitate the natural environment of the cell accurately, inside a microfluidic chip utilizing co-culturing of two human cell lines. The chemical composition of the synthesized GelMA was identified by Fourier transform infrared spectrophotometry (FTIR), its surface morphology was observed by field emission electron microscopy (FESEM), and the structural properties were analyzed by atomic force microscopy (AFM). The swelling behavior of the hydrogel in the microfluidic chip was imaged, and its porosity was examined for 72 h by tracking cell localization using immunofluorescence. GelMA exhibited the desired biomechanical properties, and the viability of cells in both platforms was more than 80% for seven days. Furthermore, GelMA was a viable platform for 3D cell culture studies and was structurally stable over long periods, even when prepared by photopolymerization in a microfluidic platform. This work demonstrated a viable strategy to conduct co-culturing experiments as well as modeling invasion and migration events. This microfluidic assay may have application in drug delivery and dosage optimization studies.

Machine Learning-Enabled Prediction of 3D-Printed Microneedle Features

Microneedles (MNs) introduced a novel injection alternative to conventional needles, offering a decreased administration pain and phobia along with more efficient transdermal and intradermal drug delivery/sample collecting. 3D printing methods have emerged in the field of MNs for their time- and cost-efficient manufacturing. Tuning 3D printing parameters with artificial intelligence (AI), including machine learning (ML) and deep learning (DL), is an emerging multidisciplinary field for optimization of manufacturing biomedical devices. Herein, we presented an AI framework to assess and predict 3D-printed MN features. Biodegradable MNs were fabricated using fused deposition modeling (FDM) 3D printing technology followed by chemical etching to enhance their geometrical precision. DL was used for quality control and anomaly detection in the fabricated MNAs. Ten different MN designs and various etching exposure doses were used create a data library to train ML models for extraction of similarity metrics in order to predict new fabrication outcomes when the mentioned parameters were adjusted. The integration of AI-enabled prediction with 3D printed MNs will facilitate the development of new healthcare systems and advancement of MNs' biomedical applications.

Three-Dimensional-Bioprinted Liver Chips and Challenges

Drug testing, either on animals or on 2D cell cultures, has its limitations due to inaccurate mimicking of human pathophysiology. The liver, as one of the key organs that filters and detoxifies the blood, is susceptible to drug-induced injuries. Integrating 3D bioprinting with microfluidic chips to fabricate organ-on-chip platforms for 3D liver cell cultures with continuous perfusion can offer a more physiologically relevant liver-mimetic platform for screening drugs and studying liver function. The development of organ-on-chip platforms may ultimately contribute to personalized medicine as well as body-on-chip technology that can test drug responses and organ–organ interactions on a single or linked chip model.

Deep Learning-Enabled Technologies for Bioimage Analysis

Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular morphology quantification is one of the pioneers. Here, we first briefly explain fundamental concepts in DL and then we review some of the emerging DL-enabled applications in cell morphology quantification in the fields of embryology, point-of-care ovulation testing, as a predictive tool for fetal heart pregnancy, cancer diagnostics via classification of cancer histology images, autosomal polycystic kidney disease, and chronic kidney diseases.