Both microplastics and phytoplankton are found together in the ocean as suspended microparticles. There is a need for deployable technologies that can identify, size, and count these particles at high throughput to monitor plankton community structure and microplastic pollution levels. In situ analysis is particularly desirable as it avoids the problems associated with sample storage, processing, and degradation. Current technologies for phytoplankton and microplastic analysis are limited in their capability by specificity, throughput, or lack of deployability. Little attention has been paid to the smallest size fraction of microplastics and phytoplankton below 10 μm in diameter, which are in high abundance. Impedance cytometry is a technique that uses microfluidic chips with integrated microelectrodes to measure the electrical impedance of individual particles. Here, we present an impedance cytometer that can discriminate and count microplastics sampled directly from a mixture of phytoplankton in a seawater-like medium in the 1.5-10 μm size range. A simple machine learning algorithm was used to classify microplastic particles based on dual-frequency impedance measurements of particle size (at 1 MHz) and cell internal electrical composition (at 500 MHz). The technique shows promise for marine deployment, as the chip is sensitive, rugged, and mass producible.

Microfluidic devices are increasingly widespread in the literature, being applied to numerous exciting applications, from chemical research to Point-of-Care devices, passing through drug development and clinical scenarios. Setting up these microenvironments, however, introduces the necessity of locally controlling the variables involved in the phenomena under investigation. For this reason, the literature has deeply explored the possibility of introducing sensing elements to investigate the physical quantities and the biochemical concentration inside microfluidic devices. Biosensors, particularly, are well known for their high accuracy, selectivity, and responsiveness. However, their signals could be challenging to interpret and must be carefully analysed to carry out the correct information. In addition, proper data analysis has been demonstrated even to increase biosensors\' mentioned qualities. To this regard, machine learning algorithms are undoubtedly among the most suitable approaches to undertake this job, automatically learning from data and highlighting biosensor signals\' characteristics at best. Interestingly, it was also demonstrated to benefit microfluidic devices themselves, in a new paradigm that the literature is starting to name \"intelligent microfluidics\", ideally closing this benefic interaction among these disciplines. This review aims to demonstrate the advantages of the triad paradigm microfluidics-biosensors-machine learning, which is still little used but has a great perspective. After briefly describing the single entities, the different sections will demonstrate the benefits of the dual interactions, highlighting the applications where the reviewed triad paradigm was employed.

UNASSIGNED: The microfluidic device is highly optimized to remove oocytes from the cumulus-corona cell mass surrounding them. Additionally, it effectively captures and immobilizes the oocytes, aiding in assessing their quality and facilitating the injection of sperm into the oocyte. In this study, a novel microfluidic chip was designed and manufactured using conventional soft lithography methods.
UNASSIGNED: This research proposes the utilization of a microfluidic chip as a substitute for the conventional manual procedures involved in oocyte denudation, trapping, and immobilization. The microfluidic chip was modeled and simulated using COMSOL Multiphysics® 5.2 software to optimize and enhance its design and performance. The microfluidic chip was fabricated using conventional injection molding techniques on a polydimethylsiloxane substrate by employing soft lithography methods.
UNASSIGNED: A hydrostatic force was applied to guide the oocyte through predetermined pathways to eliminate the cumulus cells surrounding the oocyte. The oocyte was subsequently confined within the designated trap region by utilizing hydraulic resistance along the paths and immobilized by applying vacuum force.
UNASSIGNED: The application of this chip necessitates a lower level of operator expertise compared to enzymatic and mechanical techniques. Moreover, it is feasible to continuously monitor the oocyte\'s state throughout the procedure. There is a reduced need for cultural media compared to more standard approaches.

This study presents a novel absorption cell with a circular geometry that can be integrated into microfluidic devices for optical spectroscopy applications. The absorption cell is made of PDMS/SU8 and offers an optical path length that is 8.5 times its diameter, resulting in a significant increase in the sensitivity of the measurements. Overall, this design provides a reliable and efficient solution for optical spectroscopy in microfluidic systems, enabling the precise detection and analysis of small quantities of analytes.

Intracellular and extracellular sensing of physical and chemical variables is important for disease diagnosis and the understanding of cellular biology. Optical sensing utilizing fluorescent nanodiamonds (FNDs) is promising for probing intracellular and extracellular variables owing to their biocompatibility, photostability, and sensitivity to physicochemical quantities. Based on the potential of FNDs, we outlined the optical properties, biocompatibility, surface chemistry of FNDs and their applications in intracellular biosensing. This review also introduces biosensing platforms that combine FNDs and lab-on-a-chip approaches to control the extracellular environment and improve sample/reagent handling and sensing performance.

In the context of global population growth expected in the future, enhancing the agri-food yield is crucial. Plant diseases significantly impact crop production and food security. Modern microfluidics offers a compact and convenient approach for detecting these defects. Although this field is still in its infancy and few comprehensive reviews have explored this topic, practical research has great potential. This paper reviews the principles, materials, and applications of microfluidic technology for detecting plant diseases caused by various pathogens. Its performance in realizing the separation, enrichment, and detection of different pathogens is discussed in depth to shed light on its prospects. With its versatile design, microfluidics has been developed for rapid, sensitive, and low-cost monitoring of plant diseases. Incorporating modules for separation, preconcentration, amplification, and detection enables the early detection of trace amounts of pathogens, enhancing crop security. Coupling with imaging systems, smart and digital devices are increasingly being reported as advanced solutions.

Microfluidics, also called lab-on-a-chip, represents an emerging research platform that permits more precise and manipulation of samples at the microscale or even down to the nanoscale (nanofluidic) including picoliter droplets, microparticles, and microbes within miniaturized and highly integrated devices. This groundbreaking technology has made significant strides across multiple disciplines by providing an unprecedented view of physical, chemical, and biological events, fostering a holistic and an in-depth understanding of complex systems. The application of microfluidics to address the challenges in environmental science is likely to contribute to our better understanding, however, it\'s not yet fully developed. To raise researchers\' interest, this discussion first delineates the valuable and underutilized environmental applications of microfluidic technology, ranging from environmental surveillance to acting as microreactors for investigating interfacial dynamic processes, and facilitating high-throughput bioassays. We highlight, with examples, how rationally designed microfluidic devices lead to new insights into the advancement of environmental science and technology. We then critically review the key challenges that hinder the practical adoption of microfluidic technologies. Specifically, we discuss the extent to which microfluidics accurately reflect realistic environmental scenarios, outline the areas to be improved, and propose strategies to overcome bottlenecks that impede the broad application of microfluidics. We also envision new opportunities and future research directions, aiming to provide guidelines for the broader utilization of microfluidics in environmental studies.

Heart failure represents a primary cause of hospitalization and mortality in both developed and developing countries, often necessitating heart transplantation as the only viable recovery path. Despite advances in transplantation medicine, organ rejection remains a significant post-operative challenge, traditionally monitored through invasive endomyocardial biopsies (EMB). This study introduces a rapid prototyping approach to organ rejection monitoring via a sensor-integrated flexible patch, employing electrical impedance spectroscopy (EIS) for the non-invasive, continuous assessment of resistive and capacitive changes indicative of tissue rejection processes. Utilizing titanium-dioxide-coated electrodes for contactless impedance sensing, this method aims to mitigate the limitations associated with EMB, including procedural risks and the psychological burden on patients. The biosensor\'s design features, including electrode passivation and three-dimensional microelectrode protrusions, facilitate effective monitoring of cardiac rejection by aligning with the heart\'s curvature and responding to muscle contractions. Evaluation of sensor performance utilized SPICE simulations, scanning electron microscopy, and cyclic voltammetry, alongside experimental validation using chicken heart tissue to simulate healthy and rejected states. The study highlights the potential of EIS in reducing the need for invasive biopsy procedures and offering a promising avenue for early detection and monitoring of organ rejection, with implications for patient care and healthcare resource utilization.

Legionella pneumophila has been pinpointed by the World Health Organization as the highest health burden of all waterborne pathogens in the European Union and is responsible for many disease outbreaks around the globe. Today, standard analysis methods (based on bacteria culturing onto agar plates) need several days (~12) in specialized analytical laboratories to yield results, not allowing for timely actions to prevent outbreaks. Over the last decades, great efforts have been made to develop more efficient waterborne pathogen diagnostics and faster analysis methods, requiring further advancement of microfluidics and sensors for simple, rapid, accurate, inexpensive, real-time, and on-site methods. Herein, a lab-on-a-chip device integrating sample preparation by accommodating bacteria capture, lysis, and DNA isothermal amplification with fast (less than 3 h) and highly sensitive, colorimetric end-point detection of L. pneumophila in water samples is presented, for use at the point of need. The method is based on the selective capture of viable bacteria on on-chip-immobilized and -lyophilized antibodies, lysis, the loop-mediated amplification (LAMP) of DNA, and end-point detection by a color change, observable by the naked eye and semiquantified by computational image analysis. Competitive advantages are demonstrated, such as low reagent consumption, portability and disposability, color change, storage at RT, and compliance with current legislation.

Following the relaxation of COVID-19 restrictions, other respiratory viruses such as influenza and respiratory syncytial virus (RSV), whose transmission were decreased due to COVID-19 precautions, are rising again. Because of similar clinical features and reported co-infections, multiplex detection of SARS-CoV-2, influenza A/B, and RSV is required to use specific treatments. This study assessed an extraction-free sample preparation (heat treatment at 95°C for 3 minutes) for multiplex detection using rRT-PCR. Despite an observed Ct-delay (∆Ct) averageing 1.26 compared to the standard method, an acceptable total sensitivity of 92 % and a negative predictive value (NPV) of 96 % were obtained. Moreover, Implementation on a microfluidic chip demonstrated efficiency, maintaining an excellent correlation (R2=0.983) with the standard method. Combining this extraction-free procedure with rRT-PCR on a microfluidic chip seems promising, because it simplifies the design and reduces the cost and complexity of the integrated assay for multiplex detection of SARS-CoV-2, influenza A/B, and RSV.