Nanotechnology-based electrochemical biosensors for monitoring breast cancer biomarkers.

Breast cancer is categorized as the most widespread cancer type among women globally. On-time diagnosis can decrease the mortality rate by making the right decision in the therapy procedure. These features lead to a reduction in medication time and socioeconomic burden. The current review article provides a comprehensive assessment for breast cancer diagnosis using nanomaterials and related technologies. Growing use of the nano/biotechnology domain in terms of electrochemical nanobiosensor designing was discussed in detail. In this regard, recent advances in nanomaterial applied for amplified biosensing methodologies were assessed for breast cancer diagnosis by focusing on the advantages and disadvantages of these approaches. We also monitored designing methods, advantages, and the necessity of suitable (nano) materials from a statistical standpoint. The main objective of this review is to classify the applicable biosensors based on breast cancer biomarkers. With numerous nano-sized platforms published for breast cancer diagnosis, this review tried to collect the most suitable methodologies for detecting biomarkers and certain breast cancer cell types.

Machine learning-enabled optimization of extrusion-based 3D printing.

Machine learning (ML) and three-dimensional (3D) printing are among the fastest-growing branches of science. While ML can enable computers to independently learn from available data to make decisions with minimal human intervention, 3D printing has opened up an avenue for modern, multi-material, manufacture of complex 3D structures with a rapid turn-around ability for users with limited manufacturing experience. However, the determination of optimum printing parameters is still a challenge, increasing pre-printing process time and material wastage. Here, we present the first integration of ML and 3D printing through an easy-to-use graphical user interface (GUI) for printing parameter optimization. Unlike the widely held orthogonal design used in most of the 3D printing research, we, for the first time, used nine different computer-aided design (CAD) images and in order to enable ML algorithms to distinguish the difference between designs, we devised a self-designed method to calculate the "complexity index" of CAD designs. In addition, for the first time, the similarity of the print outcomes and CAD images are measured using four different self-designed labeling methods (both manually and automatically) to figure out the best labeling method for ML purposes. Subsequently, we trained eight ML algorithms on 224 datapoints to identify the best ML model for 3D printing applications. The "gradient boosting regression" model yields the best prediction performance with an R-2 score of 0.954. The ML-embedded GUI developed in this study enables users (either skilled or unskilled in 3D printing and/or ML) to simply upload a design (desired to print) to the GUI along with desired printing temperature and pressure to obtain the approximate similarity in the case of actual 3D printing of the uploaded design. This ultimately can prevent error-and-trial steps prior to printing which in return can speed up overall design-to-end-product time with less material waste and more cost-efficiency.

Additive manufacturing and three-dimensional printing in obstetrics and gynecology: a comprehensive review.

Three-dimensional (3D) printing, also known as additive manufacturing, is a technology used to create complex 3D structures out of a digital model that can be almost any shape. Additive manufacturing allows the creation of customized, finely detailed constructs. Improvements in 3D printing, increased 3D printer availability, decreasing costs, development of biomaterials, and improved cell culture techniques have enabled complex, novel, and customized medical applications to develop. There have been rapid development and utilization of 3D printing technologies in orthopedics, dentistry, urology, reconstructive surgery, and other health care areas. Obstetrics and Gynecology (OBGYN) is an emerging application field for 3D printing. This technology can be utilized in OBGYN for preventive medicine, early diagnosis, and timely treatment of women-and-fetus-specific health issues. Moreover, 3D printed simulations of surgical procedures enable the training of physicians according to the needs of any given procedure. Herein, we summarize the technology and materials behind additive manufacturing and review the most recent advancements in the application of 3D printing in OBGYN studies, such as diagnosis, surgical planning, training, simulation, and customized prosthesis. Furthermore, we aim to give a future perspective on the integration of 3D printing and OBGYN applications and to provide insight into the potential applications.

Electrochemiluminescent immunosensor for detection of carcinoembryonic antigen using luminol-coated silver nanoparticles.

Recently, electrochemiluminescent (ECL) immunosensors have received much attention in the field of biomarker detection. Here, a highly enhanced ECL immunosensing platform was designed for ultrasensitive detection of carcinoembryonic antigen (CEA). The surface of the glassy carbon electrode was enhanced by applying functional nanostructures such as thiolated graphene oxide (S-GO) and streptavidin-coated gold nanoparticles (SA-AuNPs). The selectivity and sensitivity of the designed immunosensor were improved by entrapping CEA biomolecules using a sandwich approach. Luminol/silver nanoparticles (Lu-SNPs) were applied as the main core of the signaling probe, which were then coated with streptavidin to provide overloading of the secondary antibody. The highly ECL signal enhancement was obtained due to the presence of horseradish peroxidase (HRP) in the signaling probe, in which the presence of H2O2 further amplified the intensity of the signals. The engineered immunosensor presented excellent sensitivity for CEA detection, with limit of detection (LOD) and linear detection range (LDR) values of 58 fg mL-1 and 0.1 pg mL-1 to 5 pg mL-1 (R2 = 0.9944), respectively. Besides its sensitivity, the fabricated ECL immunosensor presented outstanding selectivity for the detection of CEA in the presence of various similar agents. Additionally, the developed immunosensor showed an appropriate repeatability (RSD 3.8%) and proper stability (2 weeks). Having indicated a robust performance in the real human serum with stated LOD and LDR, the engineered immunosensor can be considered for the detection and monitoring of CEA in the clinic.

Microfluidics for microalgal biotechnology.

Microalgae have expanded their roles as renewable and sustainable feedstocks for biofuel, smart nutrition, biopharmaceutical, cosmeceutical, biosensing, and space technologies. They accumulate valuable biochemical compounds from protein, carbohydrate, and lipid groups, including pigments and carotenoids. Microalgal biomass, which can be adopted for multivalorization under biorefinery settings, allows not only the production of various biofuels but also other value-added biotechnological products. However, state-of-the-art technologies are required to optimize yield, quality, and the economical aspects of both upstream and downstream processes. As such, the need to use microfluidic-based devices for both fundamental research and industrial applications of microalgae, arises due to their microscale sizes and dilute cultures. Microfluidics-based devices are superior to their competitors through their ability to perform multiple functions such as sorting and analyzing small amounts of samples (nanoliter to picoliter) with higher sensitivities. Here, we review emerging applications of microfluidic technologies on microalgal processes in cell sorting, cultivation, harvesting, and applications in biofuels, biosensing, drug delivery, and nutrition.

Mitochondrial donation in translational medicine; from imagination to reality.

The existence of active crosstalk between cells in a paracrine and juxtacrine manner dictates specific activity under physiological and pathological conditions. Upon juxtacrine interaction between the cells, various types of signaling molecules and organelles are regularly transmitted in response to changes in the microenvironment. To date, it has been well-established that numerous parallel cellular mechanisms participate in the mitochondrial transfer to modulate metabolic needs in the target cells. Since the conception of stem cells activity in the restoration of tissues' function, it has been elucidated that these cells possess a unique capacity to deliver the mitochondrial package to the juxtaposed cells. The existence of mitochondrial donation potentiates the capacity of modulation in the distinct cells to achieve better therapeutic effects. This review article aims to scrutinize the current knowledge regarding the stem cell's mitochondrial transfer capacity and their regenerative potential.

Continuous-Ink, Multiplexed Pen-Plotter Approach for Low-Cost, High-Throughput Fabrication of Paper-Based Microfluidics.

There is an unmet need for high-throughput fabrication techniques for paper-based microanalytical devices, especially in limited resource areas. Fabrication of these devices requires precise and repeatable deposition of hydrophobic materials in a defined pattern to delineate the hydrophilic reaction zones. In this study, we demonstrated a cost- and time-effective method for high-throughput, easily accessible fabrication of paper-based microfluidics using a desktop pen plotter integrated with a custom-designed multipen holder. This approach enabled simultaneous printing with multiple printing heads and, thus, multiplexed fabrication. Moreover, we proposed an ink supply system connected to commercial technical pens to allow continuous flow of the ink, thereby increasing the printing capacity of the system. We tested the use of either hot- or cold-laminating layers to improve (i) the durability, stability, and mechanical strength of the paper-based devices and (ii) the seal on the back face of the chromatography paper to prevent wetting of the sample beyond the hydrophilic testing region. To demonstrate a potential application of the paper-based microfluidic devices fabricated by the proposed method, colorimetric urine assays were implemented and tested: nitrite, urobilinogen, protein, blood, and pH.

Flow induces epithelial-mesenchymal transition, cellular heterogeneity and biomarker modulation in 3D ovarian cancer nodules.

Seventy-five percent of patients with epithelial ovarian cancer present with advanced-stage disease that is extensively disseminated intraperitoneally and prognosticates the poorest outcomes. Primarily metastatic within the abdominal cavity, ovarian carcinomas initially spread to adjacent organs by direct extension and then disseminate via the transcoelomic route to distant sites. Natural fluidic streams of malignant ascites triggered by physiological factors, including gravity and negative subdiaphragmatic pressure, carry metastatic cells throughout the peritoneum. We investigated the role of fluidic forces as modulators of metastatic cancer biology in a customizable microfluidic platform using 3D ovarian cancer nodules. Changes in the morphological, genetic, and protein profiles of biomarkers associated with aggressive disease were evaluated in the 3D cultures grown under controlled and continuous laminar flow. A modulation of biomarker expression and tumor morphology consistent with increased epithelial-mesenchymal transition, a critical step in metastatic progression and an indicator of aggressive disease, is observed because of hydrodynamic forces. The increase in epithelial-mesenchymal transition is driven in part by a posttranslational up-regulation of epidermal growth factor receptor (EGFR) expression and activation, which is associated with the worst prognosis in ovarian cancer. A flow-induced, transcriptionally regulated decrease in E-cadherin protein expression and a simultaneous increase in vimentin is observed, indicating increased metastatic potential. These findings demonstrate that fluidic streams induce a motile and aggressive tumor phenotype. The microfluidic platform developed here potentially provides a flow-informed framework complementary to conventional mechanism-based therapeutic strategies, with broad applicability to other lethal malignancies.

Manipulating biological agents and cells in micro-scale volumes for applications in medicine.

Recent technological advances provide new tools to manipulate cells and biological agents in micro/nano-liter volumes. With precise control over small volumes, the cell microenvironment and other biological agents can be bioengineered; interactions between cells and external stimuli can be monitored; and the fundamental mechanisms such as cancer metastasis and stem cell differentiation can be elucidated. Technological advances based on the principles of electrical, magnetic, chemical, optical, acoustic, and mechanical forces lead to novel applications in point-of-care diagnostics, regenerative medicine, in vitro drug testing, cryopreservation, and cell isolation/purification. In this review, we first focus on the underlying mechanisms of emerging examples for cell manipulation in small volumes targeting applications such as tissue engineering. Then, we illustrate how these mechanisms impact the aforementioned biomedical applications, discuss the associated challenges, and provide perspectives for further development.

Impedimetric antimicrobial peptide biosensor for the detection of human immunodeficiency virus envelope protein gp120.

This study presents the design and implementation of an antimicrobial peptide-based electrochemical impedance spectroscopy (EIS) based biosensor system. The biosensor consists of a gold coated carbon electrode with MXene and silver nanoparticles (AgNPs) for the label-free detection of the human immunodeficiency virus (HIV) envelope protein gp120. Scanning electron microscopy was used to confirm the presence and distribution of MXene and AgNPs on the biosensor surface. The employment of the antimicrobial peptide on the electrode surface minimized the denaturation of the biorecognition receptor to ensure reliable and stable performance. The biosensor exhibited a linear range of 10-4000 pg mL-1 for gp120 detection, demonstrating good repeatability in real samples. The limit of detection (LOD) and limit of quantification (LOQ) were also calculated as 0.05 pg mL-1 and 0.14 pg mL-1, respectively. This biosensing platform has promising applications in the detection of HIV in clinical and point-of-care settings.

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.

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.

Skin-on-a-chip technologies towards clinical translation and commercialization.

Skin is the largest organ of the human body which plays a critical role in thermoregulation, metabolism (e.g. synthesis of vitamin D), and protection of other organs from environmental threats, such as infections, microorganisms, ultraviolet radiation, and physical damage. Even though skin diseases are considered to be less fatal, the ubiquity of skin diseases and irritation caused by them highlights the importance of skin studies. Furthermore, skin is a promising means for transdermal drug delivery, which requires a thorough understanding of human skin structure. Current animal andin vitrotwo/three-dimensional skin models provide a platform for disease studies and drug testing, whereas they face challenges in the complete recapitulation of the dynamic and complex structure of actual skin tissue. One of the most effective methods for testing pharmaceuticals and modeling skin diseases are skin-on-a-chip (SoC) platforms. SoC technologies provide a non-invasive approach for examining 3D skin layers and artificially creating disease models in order to develop diagnostic or therapeutic methods. In addition, SoC models enable dynamic perfusion of culture medium with nutrients and facilitate the continuous removal of cellular waste to further mimic thein vivocondition. Here, the article reviews the most recent advances in the design and applications of SoC platforms for disease modeling as well as the analysis of drugs and cosmetics. By examining the contributions of different patents to the physiological relevance of skin models, the review underscores the significant shift towards more ethical and efficient alternatives to animal testing. Furthermore, it explores the market dynamics ofin vitroskin models and organ-on-a-chip platforms, discussing the impact of legislative changes and market demand on the development and adoption of these advanced research tools. This article also identifies the existing obstacles that hinder the advancement of SoC platforms, proposing directions for future improvements, particularly focusing on the journey towards clinical adoption.

Exosomes encapsulated in hydrogels for effective central nervous system drug delivery.

The targeted delivery of pharmacologically active molecules, metabolites, and growth factors to the brain parenchyma has become one of the major challenges following the onset of neurodegeneration and pathological conditions. The therapeutic effect of active biomolecules is significantly impaired after systemic administration in the central nervous system (CNS) because of the blood-brain barrier (BBB). Therefore, the development of novel therapeutic approaches capable of overcoming these limitations is under discussion. Exosomes (Exo) are nano-sized vesicles of endosomal origin that have a high distribution rate in biofluids. Recent advances have introduced Exo as naturally suitable bio-shuttles for the delivery of neurotrophic factors to the brain parenchyma. In recent years, many researchers have attempted to regulate the delivery of Exo to target sites while reducing their removal from circulation. The encapsulation of Exo in natural and synthetic hydrogels offers a valuable strategy to address the limitations of Exo, maintaining their integrity and controlling their release at a desired site. Herein, we highlight the current and novel approaches related to the application of hydrogels for the encapsulation of Exo in the field of CNS tissue engineering.

Exhaustion of racing sperm in nature-mimicking microfluidic channels during sorting.

Fertilization is central to the survival and propagation of a species, however, the precise mechanisms that regulate the sperm's journey to the egg are not well understood. In nature, the sperm has to swim through the cervical mucus, akin to a microfluidic channel. Inspired by this, a simple, cost-effective microfluidic channel is designed on the same scale. The experimental results are supported by a computational model incorporating the exhaustion time of sperm.

Machine Learning-Enabled Optimization of Interstitial Fluid Collection via a Sweeping Microneedle Design.

Microneedles (MNs) allow for biological fluid sampling and drug delivery toward the development of minimally invasive diagnostics and treatment in medicine. MNs have been fabricated based on empirical data such as mechanical testing, and their physical parameters have been optimized through the trial-and-error method. While these methods showed adequate results, the performance of MNs can be enhanced by analyzing a large data set of parameters and their respective performance using artificial intelligence. In this study, finite element methods (FEMs) and machine learning (ML) models were integrated to determine the optimal physical parameters for a MN design in order to maximize the amount of collected fluid. The fluid behavior in a MN patch is simulated with several different physical and geometrical parameters using FEM, and the resulting data set is used as the input for ML algorithms including multiple linear regression, random forest regression, support vector regression, and neural networks. Decision tree regression (DTR) yielded the best prediction of optimal parameters. ML modeling methods can be utilized to optimize the geometrical design parameters of MNs in wearable devices for application in point-of-care diagnostics and targeted drug delivery.

Bioprinting in Microgravity.

Bioprinting as an extension of 3D printing offers capabilities for printing tissues and organs for application in biomedical engineering. Conducting bioprinting in space, where the gravity is zero, can enable new frontiers in tissue engineering. Fabrication of soft tissues, which usually collapse under their own weight, can be accelerated in microgravity conditions as the external forces are eliminated. Furthermore, human colonization in space can be supported by providing critical needs of life and ecosystems by 3D bioprinting without relying on cargos from Earth, e.g., by development and long-term employment of living engineered filters (such as sea sponges-known as critical for initiating and maintaining an ecosystem). This review covers bioprinting methods in microgravity along with providing an analysis on the process of shipping bioprinters to space and presenting a perspective on the prospects of zero-gravity bioprinting.

Loop-Mediated Isothermal Amplification-Integrated CRISPR Methods for Infectious Disease Diagnosis at Point of Care.

Infectious diseases continue to pose an imminent threat to global public health, leading to high numbers of deaths every year and disproportionately impacting developing countries where access to healthcare is limited. Biological, environmental, and social phenomena, including climate change, globalization, increased population density, and social inequity, contribute to the emergence of novel communicable diseases. Rapid and accurate diagnoses of infectious diseases are essential to preventing the transmission of infectious diseases. Although some commonly used diagnostic technologies provide highly sensitive and specific measurements, limitations including the requirement for complex equipment/infrastructure and refrigeration, the need for trained personnel, long sample processing times, and high cost remain unresolved. To ensure global access to affordable diagnostic methods, loop-mediated isothermal amplification (LAMP) integrated clustered regularly interspaced short palindromic repeat (CRISPR) based pathogen detection has emerged as a promising technology. Here, LAMP-integrated CRISPR-based nucleic acid detection methods are discussed in point-of-care (PoC) pathogen detection platforms, and current limitations and future directions are also identified.

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.