Biosensors

Severe Dengue fever can cause Dengue Hemorrhagic Fever (DHF), a life-threatening condition characterized by plasma leakage and hemoconcentration. A hematocrit (Hct) rise of ≥20% is a key indicator for medical intervention, but current monitoring is invasive and intermittent. This study aims to determine the optimal design parameters for a non-invasive optical sensor to continuously monitor hemoconcentration. We developed a high-fidelity Monte Carlo model of light transport in a multi-layered skin model, with the epidermis set to a 5% melanin volume fraction (Fitzpatrick type II/III). To ensure signal reliability, simulations were conducted with a high photon count ($1\times {10}^8$ photons), yielding a stochastic (Monte Carlo) signal-to-noise ratio of approximately 36 dB. We simulated diffuse reflectance at four characteristic wavelengths (577 nm, 660 nm, 800 nm—the isosbestic point—, and 940 nm) over source-detector separations of 0.5–8.0 mm. Sensor sensitivity was quantified as the reflectance change for a +25% relative Hct rise (e.g., 42% to 52.5%), mimicking severe hemoconcentration, and its dependence on baseline dermal blood volume fraction (BVF) was investigated. Sensor sensitivity showed a non-linear dependence on BVF, showing a direct correlation with perfusion level, reaching an optimal 6.41% for a robust 5% BVF at 8.0 mm. A dedicated sweep showed that even under low-perfusion shock conditions (1% BVF), the sensor maintains a highly significant sensitivity of 5.71% (also at 8.0 mm), indicating that sensitivity remains high across a physiologically relevant perfusion range. In the analysis, at a robust 5% BVF, the 800 nm wavelength demonstrated superior reliability, with peak sensitivity at 6.41% at 8.0 mm. Visible wavelengths (577 nm and 660 nm) exhibited high theoretical sensitivity, while 940 nm was compromised by water absorption. Based on these findings, a non-invasive optical sensor for hemoconcentration is most effective operating at 800 nm, within the evaluated spectral set, with a source-detector separation of ≥6.0 mm, targeting the deep dermis while minimizing superficial interference. This design provides an optimal balance of tissue penetration, robust sensitivity to Hct changes, and reduced sensitivity to oxygenation-related variability while maintaining signal stability. This work enables the design of a device for continuous monitoring, supporting continuous monitoring of hemoconcentration trends relevant to plasma leakage progression.

Traditional sample preparation for flow cytometry is often labor-intensive, operator-dependent, and reagent-consuming, limiting its suitability for automated and point-of-care biosensing applications. To address these challenges, this study presents a functional modular microfluidic system integrating immunomagnetic beads (IMBs) to enable automated intracellular immunofluorescence (IF) staining. The modular microfluidic platform is enabled by a dynamically actuated three-dimensional magnetic field that couples with IMBs within a microfluidic reaction chamber, requiring only one-dimensional magnet translation to induce effective three-dimensional bead motion. This magnetic–chip cooperative strategy significantly enhances microscale mixing and cell capture, facilitating automated immunostaining of the radiation biomarker in CD4⁺ cells. Finite element simulations were employed to guide magnetic field design by analyzing magnetic force distributions and identifying key parameters, including magnet material, size, spatial arrangement, and chip–magnet distance. Experimental validation using CD4⁺ cell capture confirmed the effectiveness of the magnetic mixing strategy, revealing ∇B·B as the critical design parameter. An N52 NdFeB magnet (6 mm diameter, 10 mm height) positioned within 2.2 mm of the chamber centerline stably retained IMBs at flow rates below 200 µL/min. Under optimized conditions (magnet translation speed of 8 mm/s and a 15 min mixing duration), a maximum cell capture efficiency of 86% was achieved. Subsequent automated γH2AX IF staining demonstrated a strong linear dose–response relationship (R² > 0.9) in mean fluorescence intensity. This study demonstrates a robust and scalable strategy for automating complex IF staining workflows, highlighting the potential of magnetic-field-assisted microfluidic platforms for biosensing applications requiring reliable intracellular biomarker detection.

Correct focal positioning is essential for microscopy imaging of live moving subjects such as Caenorhabditis elegans. However, many methods can be too slow to perform real-time control to keep the subject in focus. In this work, we propose a convolutional neural network-based method to perform one-shot prediction of the optimal focusing distance, without the need to scan iteratively the optical axis to find the optimal position. A new data augmentation technique is proposed, and its effectiveness is validated through statistical analysis. This technique is shown to improve results without the need for additional data collection. Several architectures are trained in z-stacks of images, using the proposed data augmentation technique, and compared on a validation set. Through this comparison, we find that the ConvNext V2, a novel architecture in this context, outperforms other models proposed in previous works. Furthermore, the impact of the Field of View used for the model’s prediction is studied, with the aim of further understanding the influence of spatial resolution and spatial compression on the performance of the model.