Search Results (276)

Antimicrobial resistance (AMR) is an ever-growing threat to global healthcare. It is largely driven by delayed or inadequate pathogen identification and antimicrobial susceptibility testing in routine clinical workflows. By the time the clinician receives results to guide treatment from traditional culture-based diagnostics, several days may have elapsed, leading to the use and potential over-prescription of broad-spectrum antibiotics and the development of resistant pathogens. A rapid and clinically actionable diagnostic approach at the clinical point of care (POC) may help address this gap. This review examines current and emerging POC diagnostic technologies for AMR and outlines the fundamental principles and mechanistic classifications of POC diagnostic technologies. These include phenotypic, genotypic, immunological, and biosensor-based approaches. A critical overview of key technological platforms, including rapid phenotypic antimicrobial susceptibility testing (AST), microfluidics and isothermal nucleic acid amplification (e.g., LAMP and RPA), CRISPR-based diagnostics, nanomaterial-enhanced biosensors, and mobile-integrated systems is provided. The impact of POC diagnostics on antimicrobial stewardship, time to appropriate therapy, and patient outcomes in primary care settings, hospitals, intensive care units, and resource-limited settings is presented and discussed. In addition to clinical implementation challenges, this review considers the issues of analytical performance, workflow, regulatory pathways, cost, and implementation readiness. In addition, it outlines key trends regarding digital integration, surveillance, workforce training, and policy frameworks. Overall, the review outlines the role of POC diagnostics in enhancing antimicrobial response surveillance and the global fight against AMR. Among emerging platforms, rapid phenotypic AST, microfluidic and isothermal-based assays, CRISPR-based diagnostics, and integrated biosensor systems show the greatest potential for near-term clinical impact; however, widespread implementation remains constrained by challenges related to clinical validation, cost, workflow integration, and alignment with antimicrobial stewardship frameworks. Full article

Precise manipulation of two-phase flow in micro-confined electrowetting pixels is limited by contact angle hysteresis (CAH). To elucidate this non-equilibrium process, we establish a high-fidelity electrohydrodynamic (EHD) phase-field simulation framework. The model rigorously couples Navier–Stokes equations with molecular kinetic theory (MKT) to characterize energy dissipation at the three-phase contact line (TCL) and further integrates charge transport kinetics. Numerical results reveal CAH is driven by physical pinning and interfacial charge trapping, with the latter dominating interfacial retreat and causing significant residual displacement. Furthermore, analysis shows alternating current (AC) waveforms mitigate charge accumulation and promote depinning via micro-oscillations, minimizing the hysteresis loop compared to direct current (DC) waveforms. Additionally, an overdrive strategy utilizing a suprathreshold Maxwell stress pulse rapidly overcomes static friction. This strategy significantly improves transient dynamics, substantially reducing the time to reach 90% of the steady-state target from 19.6 ms (under standard DC waveform driving) to 7.4 ms. This work provides a comprehensive theoretical basis and design criteria for optimizing active driving strategies in optofluidic and digital microfluidic systems. Full article

Personalized transdermal drug delivery systems (TDDS) represent a transformative approach in precision medicine by enabling patient-specific, non-invasive, and controlled therapeutic administration. Conventional transdermal patches are limited by fixed dosing, passive diffusion, and interindividual variability in skin permeability and metabolism, often leading to suboptimal therapeutic outcomes. Recent advances in materials science, nanotechnology, microneedle engineering, and digital health have enabled the development of next-generation personalized TDDS capable of programmable, adaptive, and feedback-controlled drug release. Smart wearable patches integrating biosensors, microfluidics, microneedles, and wireless connectivity allow real-time monitoring of physiological and biochemical parameters, enabling closed-loop drug delivery tailored to individual metabolic profiles. Nanocarriers such as lipid nanoparticles, polymeric nanoparticles, and stimuli-responsive hydrogels further enhance drug stability, penetration, and controlled release, while 3D-printing technologies facilitate patient-specific customization of patch geometry, drug loading, and release kinetics. Artificial intelligence (AI) and machine learning tools are increasingly being employed to predict drug permeation behavior, optimize enhancer combinations, and personalize dosing regimens based on pharmacogenomic and pharmacokinetic data. Despite these advances, regulatory complexity, manufacturing standardization, long-term biocompatibility, and cybersecurity considerations remain critical challenges for clinical translation. This review highlights recent innovations in personalized TDDS, discusses their clinical potential, and examines regulatory and technological barriers. Collectively, these emerging smart transdermal platforms offer a promising pathway toward adaptive, patient-centered therapeutics that can significantly improve treatment efficacy, safety, and compliance. Future research should focus on integrating multimodal biosensing, advanced biomaterials, scalable manufacturing strategies, and robust regulatory frameworks to enable clinically validated, fully autonomous transdermal systems that can dynamically adapt to real-time patient needs in diverse therapeutic settings. Full article

The implementation of stringent regulatory policies for foodborne pathogens necessitates ultra-sensitive analytical methods. Digital detection, characterized by absolute quantification and tolerance to complex matrices, serves as a robust approach for food safety monitoring. This review summarizes recent advances in digital detection for foodborne pathogens, including nucleic acid amplification-based platforms such as droplet digital PCR and digital isothermal amplification, as well as emerging preamplification-free approaches based on enzyme-mediated signal conversion, functional nanomaterials, and microfluidic devices. We also profile the applications of digital detection technologies for achieving highly specific and accurate detection of foodborne pathogens and discuss their capabilities in viable bacteria quantification, antimicrobial resistance analysis, and multiplex detection. We finally discuss emerging trends, including partition-free digital detection and artificial intelligence-assisted analysis. These advances are expected to promote the development of intelligent and data-driven food safety surveillance strategies. Full article

Droplet manipulation constitutes a fundamental operation in numerous bio-microfluidic applications, including but not limited to medical diagnostics and targeted drug delivery. Among the various technologies developed for this purpose, magnetic digital microfluidics (MDMF) has emerged as a compelling approach due to its inherent advantages of contamination-free actuation, low cost, and configurational flexibility. Nevertheless, conventional MDMF remains constrained by its reliance on bulky instrumentation and substantial power consumption for generating controllable magnetic fields, which limit its in-field applications. To address these limitations, this work presents a programmable and portable electromagnetic microfluidic droplet manipulation platform that synergistically integrates static and dynamic magnetic fields to enable non-contact, high-precision droplet control under ultra-low power conditions. The proposed system comprises an electromagnetic actuation module, a permanent magnet, and a glass substrate coated with Teflon film. The entire system is secured by a PMMA support structure, within which a glass substrate is mounted and spatially separated from the permanent magnet. The PMMA support is fabricated using a milling process, offering a simple manufacturing procedure and high structural reusability and reproducibility. The control logic is implemented on a field-programmable gate array (FPGA) development board, facilitating fully autonomous operation powered by a standard battery. The platform operates at a low voltage of 3.5 V and a driving current of 180 mA, corresponding to a total power consumption of merely 0.63 W, while achieving robust manipulation of droplets in the volume range of 0.5 to 5 μL. A maximum average droplet velocity of up to 0.6 cm/s was attained under optimal conditions. The proposed platform offers a scalable and energy-efficient solution for portable droplet-based assays and holds significant promise for integration into point-of-care diagnostic tools and field-ready biochemical analysis systems. The platform demonstrates excellent operational stability and reproducibility, as validated by repeated actuation experiments with a positioning deviation of approximately 0.1 mm under optimized conditions. The fabrication process also exhibits high reliability with consistent performance across multiple experimental runs. Full article

Organ-on-a-chip (OoC) technologies, also termed microphysiological systems (MPSs), integrate microfluidics, engineered biomaterials, human-derived cells, and on-chip biosensing to model human physiology in microscale devices that deliver quantitative, time-resolved readouts. This review surveys the 2010–2025 literature, emphasizing how sensing, standardized sampling, and analytics enable clinical concordance and fit-for-purpose regulatory use. We synthesize advances in (i) materials, fabrication, and microfluidic design; (ii) organ- and disease-focused case studies; and (iii) translational benchmarks that align chip outputs with clinical pharmacokinetics, toxicology, and biomarker datasets. Across organ systems, platforms increasingly incorporate vascularization, immune components, and organoid hybrids, paired with real-time measurements of barrier integrity, metabolism, electrophysiology, and secreted biomarkers using impedance (TEER), electrochemical, and optical modalities. Representative benchmarking studies report cardiac OoCs achieving AUROC ≥ 0.85 for torsadogenic risk classification, and renal chips improving prediction of transporter-mediated clearance relative to conventional in vitro assays. We summarize validation approaches and regulatory developments relevant to new approach methodologies, including the FDA Modernization Act 2.0, and discuss how AI and multi-omics can automate signal and image analysis, harmonize cross-platform datasets, and support digital-twin workflows that couple OoC measurements to in silico models. Overall, biosensor-enabled OoCs are progressing toward quantitatively benchmarked platforms for safety pharmacology, ADME/PK–PD, and precision medicine. Full article

Serial flow cytometry was recently introduced as a method that can estimate measurement uncertainty (i.e., imprecision, the coefficient of variation of repeated measurements of individual particles) independent from population characteristics. Replication of light sources and detectors at multiple sites along a flow cytometer’s microchannel requires more equipment and can complicate detector synchronization. Here, we introduce amplitude modulation to encode each region of a serial cytometer with a unique carrier frequency, which enables demultiplexing of the combined signal incident on a single photodetector by fast Fourier transform (FFT) peak magnitude. To facilitate validation of detection, matching, and uncertainty quantification of fluorescence signals, we designed a microfluidic amplitude modulation (AM) serial flow cytometer that has ground truth detectors on individual regions (serial cytometry) in parallel with the combined channel detection for AM demultiplexing. With this report, we present metrics for event detection and dynamic range, prevalence and processing of overlapping detections, region-decoding accuracy, process yield, and uncertainty quantification on a brightness ladder of calibration microspheres. Despite being operated with reduced light intensities, the AM cytometer was capable of high-fidelity performance in comparison to conventional serial cytometry. For events above the detection limit, over 97% were analyzed. Both conventional and AM serial cytometers achieved median imprecisions in the range of 0.53% to 2.1% after outlier removal, which was well below the inherent intensity distribution of any of the microsphere subpopulations. Overall, AM cytometry supports uncertainty quantification and temporal analyses of serial cytometry data with a reduced number of photodetectors, which offers simplification of chip design with multiple measurement regions and wide-field detectors. Full article

Artificial intelligence (AI) is reshaping healthcare by supporting faster and more informed clinical decisions. However, the complexity of human health makes accurate predictive modeling challenging. In this study, we introduce a methodological framework for constructing intelligent digital twins of disease progression by combining patients’ sequential medical images with temporally aligned electronic health records (EHRs). EHRs in this context include structured clinical parameters such as laboratory test results, demographic characteristics, and medication information. The existing literature provides limited approaches that jointly forecast future medical images and clinical status using long-term historical data. Our framework integrates aligned temporal image sequences with these EHR features and employs either ConvLSTM or ViViT-based spatio-temporal encoders, optionally coupled with a generative module for future image synthesis. While awaiting access to patient datasets, we conducted an initial evaluation using a single-cell time-lapse microscopy dataset whose temporal dynamics resemble patient data. Both systems generate time-ordered image sequences that evolve under changing conditions, and the shifting nutrient environment in microfluidic channels parallels the temporal variations observed in patients’ EHR records. This preliminary study demonstrates the broader applicability of our model to datasets containing long-term sequential images and associated parameters, supporting its potential for future patient-specific digital twin development. Full article

Digital microfluidic biochips are widely used for automated biochemical and diagnostic applications such as molecular analysis, immunoassays, and point-of-care testing. Among them, micro-electrode-dot-array (MEDA) biochips enable fine-grained droplet manipulation with shape-dependent velocity, which significantly increases routing flexibility but also computational complexity. This work proposes an efficient droplet routing method for MEDA biochips that reduces computational time while maintaining or improving solution quality. The proposed method introduces a guidance constraint that consistently directs droplets toward the target cell and integrates a solver-friendly model with a tight lower-bound design. Experimental results demonstrate that, for instances solvable by the existing method, the proposed method achieves comparable or better Routing time while reducing Solution-finding time by 72.3%. Moreover, the Solution-finding rate improves from 33.3% to 85.3% over all problem instances. Notably, for instances that cannot be solved within the time limit by the existing method, the proposed method successfully finds optimal solutions in 72.7% of the cases. These results indicate that the proposed method enables faster solution discovery, and extends solvability to previously intractable routing problems. Full article

Candida albicans is a major fungal pathogen associated with vulvovaginal candidiasis, and rapid, sensitive detection remains challenging, particularly in amplification-free formats. Here, we report NaPddCas, a microfluidic-free, droplet-based CRISPR/Cas12a detection strategy for qualitative identification of Candida albicans DNA. Unlike conventional bulk CRISPR assays, NaPddCas partitions the reaction mixture into vortex-generated polydisperse droplets, enabling spatial confinement of Cas12a activation events and effective suppression of background fluorescence. This compartmentalization substantially enhances detection sensitivity without nucleic acid amplification or microfluidic devices. Using plasmid and genomic DNA templates, NaPddCas achieved reliable detection at concentrations several orders of magnitude lower than bulk CRISPR/Cas12a reactions. The assay further demonstrated high specificity against non-target bacterial and fungal species and was successfully applied to clinical vaginal secretion samples. Importantly, NaPddCas is designed as a qualitative or semi-qualitative droplet-dependent digital detection method rather than a quantitative digital assay. Owing to its simplicity, sensitivity, and amplification-free workflow, NaPddCas represents a practical approach for laboratory-based screening of Candida albicans infections. Full article

This paper presents a multichannel electronics measurement system that uses microwave sensors to perform real-time microplastics assessment in aqueous environments. The system is capable of simultaneously reading up to four microwave sensors, enabling the use of multiple sensors that target microplastic particles with different sizes and properties. The multichannel capability allows the measurement of multiple MW sensors integrated with different microfluidic channel designs while targeting different MPs’ dimension ranges, although experimental validation in this work was limited to a single sensor. Each readout channel is implemented combining radio-technology-integrated circuits with a microprocessor that has advanced analog peripherals used for signal conditioning and acquisition. An ADF4351 wideband frequency synthesizer is used for excitation signal generation while an ADL5902 power detector converts the sensor output to a DC voltage. Baseline removal and amplification of the power detector output is realized with a MSP430FR2355 microprocessor which is also responsible for its acquisition at 40 kHz and digital decimation. Characterization results show the system’s capability to generate excitation signals between 700 MHz and 3.5 GHz with power levels around 0 dBm. Sensor output can be detected with a power between −50 dBm and −5 dBm and a 230 Hz bandwidth. A compact form factor of 15 cm × 10 cm × 3 cm was realized together with a low power consumption of 6.6 W. Validation was realized with a previously developed microwave sensor, demonstrating the detection of polyethylene spheres with 400 μm diameters animated in 10 mL/min flux within the microfluidics device. Full article

In this work, a 3D microfluidic paper-based analytical device (3D-µPAD) was developed for the smartphone-based colorimetric determination of phosphate in environmental samples. The assay relied on the formation of a blue-colored product (molybdenum blue) in the detection area of the 3D-µPAD upon reduction of the heteropolyacid H₃PMo₁₂O₄₀ formed in the presence of phosphate. A number of experimental parameters were optimized, including geometric aspects of 3D-µPADs, digitization and image processing conditions, the amount of chemicals deposited in specific areas of the 3D-µPAD, and the reaction time. In addition, the stability of the device was evaluated at three different storage temperatures. Under optimal conditions, the working range was found to be from 4 to 25 mg P/L (12–77 mg PO₄⁻³/L). The limits of detection (LOD) and quantification (LOQ) were 0.015 mg P/L and 0.05 mg P/L, respectively. The repeatability and intermediate precision of a 5 mg P/L standard were 4.8% and 7.1%, respectively. The proposed colorimetric assay has been successfully applied to phosphorous determination in various waters, soils, and sediments, obtaining recoveries in the range of 94 to 107%. The ready-to-use 3D-µPAD showed a greener profile than the standard method for phosphate determination, being affordable, easy-to-use, and suitable for citizen science applications. Full article

Droplet microfluidics enables high-throughput, compartmentalized reactions using minimal reagent volumes, but most implementations rely on precision-fabricated chips and external pumping systems that limit portability and accessibility. Here, we present a handheld vibrational droplet generator that repurposes a consumer electric toothbrush and a modified disposable pipette tip to produce nearly monodisperse water-in-oil droplets without microfluidic channels or syringe pumps. The device is powered by the toothbrush’s built-in motor and controlled by a simple 3D-printed adapter and adjustable counterweight that tune the vibration amplitude transmitted to the pipette tip. By varying the aperture of the pipette tip, droplets with diameters from ~100–300 µm were generated at rates of ~100 droplets s⁻¹. Image analysis revealed narrow size distributions with coefficients of variation below 5% in typical operating conditions. We further demonstrate proof-of-concept applications in digital loop-mediated isothermal amplification (LAMP) and microbiological colony-forming unit (CFU) assays. A commercial feline parvovirus (FPV) kit manufactured by Beyotime Biotechnology Co., Ltd. (Shanghai, China), three template concentrations yielded emulsified reaction droplets that remained stable at 65 °C for 45 min and produced distinct fractions of fluorescent-positive droplets, allowing estimation of template concentration via a Poisson model. In a second set of experiments, the device was used as a droplet-based spreader to dispense diluted Escherichia coli suspensions onto LB agar plates, achieving uniform colony distributions across the plate at different dilution factors. The proposed handheld vibrational generator is inexpensive, easy to assemble from off-the-shelf components, and minimizes dead volume and cross-contamination because only the pipette tip contacts the sample. Although the current prototype still exhibits device-to-device variability and moving droplets in open containers complicate real-time imaging, these results indicate that toothbrush-based vibrational actuation can provide a practical and scalable route toward “lab-in-hand” droplet assays in resource-limited or educational settings. Full article

Vascular diseases (VDs) and cardiovascular diseases (CVDs) are the leading causes of morbidity and mortality worldwide. Current diagnostic and therapeutic approaches are limited by insufficient resolution and a lack of mechanistic understanding at the cellular level. Traditional imaging and clinical assays do not fully capture the dynamic molecular and structural complexities underlying vascular pathology. Recent technological innovations, including single-cell and spatial transcriptomics, super-resolution and photoacoustic imaging, microfluidic organ-on-chip platforms, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-based gene editing, and artificial intelligence (AI), have created new opportunities for investigating the cellular and molecular basis of VDs. These techniques enable high-resolution mapping of cellular heterogeneity and functional alterations, facilitating the integration of large-scale data for biomarker discovery, disease modeling, and therapeutic development. This review focuses on evaluating the translational readiness, limitations, and potential clinical applications of these emerging technologies. Understanding the cellular and molecular mechanisms of VDs is essential for developing targeted therapies and precise diagnostics. Integrating single-cell and multiomics approaches highlights disease-driving cell types and gene programs. Optogenetics and organ-on-chip platforms allow for controlled manipulation and physiologically relevant modeling, while AI enhances data integration, risk prediction, and clinical interpretability. Future efforts should prioritize multi-center, large-scale validation studies, harmonization of assay protocols, and integration with clinical datasets and human samples. Multi-omics approaches and computational modeling hold promise for unraveling disease complexity, while advances in regulatory science and digital simulation (such as digital twins) may further accelerate personalized medicine in vascular disease research and treatment. Full article

Background/Objectives: Advanced drug delivery systems (DDSs) are essential for targeted delivery, controlled release, and reduced systemic toxicity, but their clinical adoption is limited by biological barriers, manufacturing complexities, and cost. The aim of this systematic review is to critically evaluate the quantitative relationships between platform design, overcoming biological barriers, and clinical translation outcomes for DDS developed between 2016 and 2025. Methods: A comprehensive literature search was conducted in PubMed/MEDLINE, Scopus, and Web of Science (January 2016–April 2025) in accordance with the PRISMA 2020 guidelines. Included studies focused on experimental or clinical data for nanocarrier platforms (liposomes, lipid nanoparticles, polymer systems, biomimetic carriers, extracellular vesicles). Data on platform characteristics, interactions with barriers, pharmacokinetics, manufacturing, and clinical outcomes were extracted and synthesized in narrative form due to the significant methodological heterogeneity. Results: An analysis of 77 included studies confirms that successful clinical translation depends on matching the physicochemical properties of the carrier (size, surface chemistry, material) to specific biological barriers. Liposomes and lipid nanoparticles (LNPs) remain the most clinically validated platforms, exploiting the EPR effect and liver tropism, respectively. Key engineering solutions include stealth coatings, ligand-mediated targeting, and stimulus-responsive materials to overcome barriers such as mononuclear phagocyte system clearance, the blood–brain barrier, and mucosal barriers. Microfluidic and continuous manufacturing processes enable reproducibility, but scalability, cost, and immunogenicity (e.g., anti-PEG responses) remain key translational challenges. Engineered extracellular vesicles, biomimetic carriers, and 3D/4D-printed systems combined with AI-driven design demonstrate the potential for personalized, adaptive delivery. Conclusions: Cutting-edge DDSs have validated their clinical value, but realizing their full potential requires a holistic, patient-centered design approach integrating barrier-specific engineering, scalable manufacturing, and rigorous safety assessment from the earliest stages of development. Further progress will depend on standardizing methods for new platforms (e.g., extracellular vesicles), implementing digital and AI tools, and ensuring translational feasibility as a fundamental principle. Full article