Biosensors and Bioelectronics

Non-small-cell lung cancer (NSCLC) diagnosis is challenged owing to the need for reliable, non-invasive biomarkers. Circulating cell-free microRNAs (ccf-miRNAs) are promising candidates, but their low levels and short sequences in blood complicate detection. In this study, a novel nano-hybrid fluorescent array was developed to enable rapid and sensitive identification of NSCLC-related ccf-miRNAs. The array consists of poly(T)-modified fluorescent nano-polystyrene beads for capturing target miRNAs, and fluorophore-labeled, sequence-specific locked nucleic acid (LNA) probes for their detection. This design forms a sandwich structure with the target miRNA. Nano cytometry and fluorescence microscopy assessed both the capture and specificity of detection. The assay was tested on plasma samples for miR-16-5p and U6, evaluating selectivity, sensitivity, and reproducibility. The results showed that the poly(T)-modified beads efficiently captured the target miRNAs, and the LNA probes accurately distinguished the sequences. The assay enabled direct detection of miR-16-5p and U6 from plasma without amplification, demonstrating high selectivity, sensitivity, and reproducibility. Combining enrichment with nano-polystyrene beads and sequence-specific LNA probes addressed the main challenges of ccf-miRNA detection, namely their low abundance and short sequence length. As ccf-miRNAs are linked to NSCLC progression, this method could assist in early diagnosis, disease monitoring, and assessment of treatment response. The target-independent nature of the poly(T) capture layer allows for easy calibration to new miRNAs by changing the LNA probes, rendering it suitable for multiplex detection in clinical settings. However, further preclinical and clinical studies are needed before adoption in routine practice. This nano-hybrid fluorescent array presents a rapid and reliable approach for detecting low-abundance ccf-miRNAs in plasma. Its encouraging performance and flexible design show potential for future application in NSCLC diagnosis and monitoring, subject to additional confirmation.

Surface plasmon resonance (SPR) and biolayer interferometry (BLI) are well-established label-free analytical technologies used to determine biomolecular interaction rates (ka, kd) and equilibrium constants (KD). While assays historically rely on multi-cycle kinetics (MCK), this approach requires intermediate surface regeneration, risking sensor degradation and increasing reagent consumption. Single-cycle kinetics (SCK) avoids regeneration by sequentially injecting increasing analyte concentrations. However, implementing SCK workflows on biosensor platforms like the OctetRR8 BLI instrument (Sartorius) remains a challenge due to the lack of built-in or online data analysis tools. To address this, we introduce SCKAnalyzer, a free, user-friendly web application designed for processing and fitting SCK datasets. SCKAnalyzer accepts column-based text files and native raw BLI data (.frd format) from Sartorius instruments, performing data pre-processing and non-linear fitting to a 1:1 interaction model. Additionally, it offers advanced simulation capabilities that allow variable association and dissociation durations across sequential injection steps, a feature absent in existing platforms such as BiacoreTMSimul8. The performance of SCKAnalyzer was experimentally validated using a 3-step SCK method (SCK3) for DNA/RNA duplex formation on a Biacore T200, as well as 4-step (SCK4) and 5-step (SCK5) methods for DNA/DNA duplex formation on an OctetRR8 BLI instrument. Binding parameters (ka, kd, KD) derived from SCKAnalyzer showed excellent agreement with values from established proprietary softwares such as Biacore T200 Evaluation Software v3.2.1 and BIAevaluation v4.1.1. SCKAnalyzer provides a practical alternative to MCK, reducing probe consumption and extending SCK utility across biosensor platforms. SCKAnalyzer is available at sck.iecb.u-bordeaux.fr (source code: github.com/synthaze/sckanalyzer).

Fermentation is a process through which microorganisms are used to transform basic molecules into high value substances in various applications such as biopharma, food production, and biofuel generation. In such processes, monitoring the health of microbial cells is essential, as it is a key factor in the final product yield. Traditional methods of assessing the health of fermenter populations have involved manually extracting samples from the fermenter for benchtop testing, which lacked the accuracy and efficacy of real-time continuous measurements. This has opened the door for inline sensors to be integrated into fermenters for continuous measurement; including microfluidic based Electrochemical Impedance Spectroscopy (EIS). EIS utilizes a range of frequencies to gain insight into the characteristics of microbial populations, such as cell size and membrane capacitance. EIS cytometry, in particular, has emerged as a relevant tool, as it enables single-cell level detection in real-time. However, current EIS cytometry devices cannot be deployed directly within fermenters due to the high cell density conditions. This has limited EIS analysis in fermenters to bulk measurements averaged across a population. Here, we present a microfluidic chip that uses passive cell-flux-partitioning geometry to direct cells from high-density culture through a single-cell-constrained flow path containing integrated impedance-sensing electrodes. The proposed chip combines geometric channel design and embedded electrodes to enable continuous impedance measurements from cell-containing flow while operating at input cell densities on the scale of 10^9 CFU/mL. This work demonstrates a first step toward integrating single-cell-constrained microfluidic handling with impedance sensing for inline monitoring in industrial biomanufacturing.

Paper-based colorimetric sensors offer a low-cost and accessible platform for point-of-care (POC) analysis, but enzyme activity loss during coating and drying can weaken analytical signals and require high enzyme loadings or complex immobilization procedures. Although surfactants are widely used to improve wettability in paper-based assays, their potential contribution to colorimetric performance beyond these effects remains unclear. Here, we investigated surfactant-assisted colorimetric signal enhancement in a glucose assay implemented on a 96-puddle paper plate (96-PPP) and identified Tween 20 as the most effective surfactant. Its effect on detection performance became more pronounced as glucose oxidase (GOx) loading decreased; at 0.1 mg/mL GOx, Tween 20 lowered the limit of detection (LoD) from 0.113 to 0.034 mg/mL (approximately 3.3-fold) over a working range of 0-5 mg/mL, despite no statistically significant change in the measured contact angle at this loading. Tween 20 had no appreciable effect on the reaction in solution but preserved 95% of the apparent reaction rate constant after drying, compared with 11% without it, and atomic force microscopy (AFM) revealed a more dispersed dried enzyme morphology on mica. Tween 20-containing sensors also showed slower signal decay during repeated wetting-drying cycles and thermal stress, retained 77% (vs 26%) of the response at 400 mM NaCl, and exhibited within-PPP and between-batch coefficients of variation (CVs) below 10% (vs 12.3-19.5%), while maintaining glucose selectivity over potentially interfering molecules. These results indicate that Tween 20 enhances paper-based glucose sensing beyond wettability, in part by retaining enzyme cascade activity during drying, although the contributions of the individual enzymes and the underlying mechanism remain to be established.

Continuous biomarker monitoring with affinity biosensors remains limited by probe saturation, slow dissociation, signal carryover, and regeneration methods that require chemical washing, harsh buffers, or external reset modules. Here, we report a flow-programmed, self-regenerative electrochemical aptamer-based biosensor for continuous 17{beta}-estradiol monitoring. The platform restores the sensing interface by tuning buffer flow through the device, enabling repeated sensing-regeneration cycles without chemical stripping or active-reset hardware. The biosensor achieves a 1.46 pM limit of detection, and a log-linear dynamic range from 100 pM to 1 M in real human sweat, covering physiologically relevant estradiol concentrations. It exhibits high selectivity, with responses to potential molecularly similar interferents remaining below 10% of the 17{beta}-estradiol signal. Under dynamic flow operation, the device shows reversible signal recovery and stable electrochemical performance, with higher buffer-wash flow reducing baseline carryover between measurements. A coupled binding-transport simulation captures the flow-dependent regeneration trends and maps how wash-flow rate, wash duration, and apparent aptamer affinity affect regeneration efficiency. Ex vivo testing in real human sweat, including samples from pregnant women, supports translational relevance. This work establishes buffer-flow programming as a reagent-free route to regenerable electrochemical aptamer sensing for automated, wearable-compatible estradiol monitoring.

Studying algae requires specialized equipment to characterize culture growth and physiological performance and non-invasive monitoring of these cultures typically relies on optical density (OD) measurements. Currently, OD is often measured using standard spectrometers that suffer from detector saturation at high cell densities, which requires time consuming sample dilutions and lacks compatibility with flat-walled cell culture flasks like Roux bottles. Here we describe a 3D-printable device to measure optically dense algal cultures directly within these cultivation vessels. This instrument combines light attenuation and scattering, resulting in a dual-sensor system that utilizes near-infrared light (950 nm) to precisely quantify biomass without interference from changing photosynthetic pigments. Cultures that reach high cell densities can be assumed to be accurately quantified in situ using the scattered signal, preserving the integrity of the culture and eliminating the need for subsampling. This method is adaptable to the most common geometries of Roux bottles (T-25, T-75, and T-175) and could be used to monitor small-scale batch cultures without contamination risks. A cyanobacteria algal species (Limnospira platensis) and three flask sizes were analysed on light attenuation linearity and scattering detection limits at different cell concentration, demonstrating that the light attenuation module can reliably measure biomass up to an OD of 3.1 (equivalent to >1.5 g/L) without requiring dilution.

Perovskite quantum dots (PQDs) are exceptionally promising next-generation optical materials for bioimaging applications. This paper presents an optical PQDs nanocomposite method to identify bacterial species associated with breast cancer, employing a LSTM deep learning model. The results indicate that the developed PQD-based nano-sensor offers impressive sensitivity, selectivity, and practical application. The four bacterial species identified in the study, Pseudomonas aeruginosa, Vibrio parvula, Acinetobacter baumannii, and Streptococcus vestibularis, were considered the most relevant indicators of breast cancer. With rapid detection, an intuitive design, and improved reliability, the PQD sensor could be an excellent breast cancer diagnostic tool for a point-of-care application. Furthermore, it has the potential to be integrated into healthcare systems, specifically in resource-limited settings, thereby improving the accessibility and efficiency of early breast cancer detection.

Hormone dynamics are central to a multitude of conditions in women's health; however, limitations in the cost, convenience, and multiplexing capacity of current hormone assays preclude routine longitudinal hormone testing. This limitation severely restricts our understanding in this historically neglected field, presenting a need for improved bioanalytical tools to support hormone-informed care. Silicon photonic resonator sensors have excellent multiplexing capacity and scalable fabrication, and offer strong potential to meet this important need. Here we demonstrate, for the first time, multiplexed silicon photonic detection of two urinary hormone biomarkers, follicle-stimulating hormone (FSH) and pregnanediol-3-glucuronide (PdG), using sub-wavelength grating ring resonators and a polydopamine-based, regenerable surface chemistry. We combine a sandwich immunoassay for FSH and an antigen-down competitive immunoassay for PdG on the same chip, both amplified using a commercially available quantum-dot-streptavidin conjugate and with on-chip regeneration over multiple measurement cycles. In artificial urine, this proof-of-principle multiplexed assay achieves limits of detection of 0.594 ng/mL for FSH and 19.1 ng/mL for PdG. This architecture is inherently scalable to tens of hormone targets on a millimetre-scale chip (a >10x multiplexing improvement over typical lateral-flow immunoassays) enabling future low-cost, quantitative at-home hormone panels that could transform research, diagnostics, and treatment in women's health.

Unlike nucleic acids, proteins cannot be directly amplified. Ultrasensitive detection must therefore couple efficient analyte-to-signal conversion with strong suppression of target-independent background. Consistently detecting ~100 molecules (below which Poisson sampling noise alone causes CV to exceed 10%) across protein targets in a format as scalable and accessible as PCR remains unsolved. Separation-based ultrasensitive immunoassays require target binding stable enough to survive stringent washing and are therefore constrained by wash-induced signal loss and, more fundamentally, the relative scarcity of exceptionally tight binders. Performance consequently varies across targets; detection limits below 1,000 molecules remain rare. Conventional separation-free proximity assays avoid washing but incur background from random probe collisions, with reported detection limits frequently exceeding 100,000 molecules. Here we introduce Successive Proximity Extension Amplification Reaction (SPEAR), a separation-free architecture in which autonomous engineered DNA nanodevices emulate biological kinetic proofreading. Two successive irreversible proximity-extension steps compound discrimination between analyte-dependent and background reactions, suppressing spurious signals while preserving efficient analyte-to-signal conversion. This design reduces reliance on high-affinity binders and enables sub-fM detection from 1 uL samples through simple 3-step mixing followed by standard qPCR readout. Across 11 biomarkers tested, SPEAR consistently achieved sub-100-molecule detection limits. Where compared, it outperformed ultrasensitive separation-based platforms, analytically and clinically, including for low-abundance Alzheimer's disease biomarkers. SPEAR also precisely quantified SARS-CoV-2 neutralizing antibody titers from finger-prick dried blood spots, concordant with the cell-based reference assay on venous blood. It detected a distinct mixed phosphorylation state of Tau, and targeting this state resolved previously observed capillary-venous discordance and improved amyloid-status discrimination. These results establish engineered autonomous successive molecular discrimination as a practical strategy for near-single-molecule protein detection, extending the sensitivity, scalability and accessibility of PCR-based testing to non-amplifiable analytes.

Finite-bandgap charge-based FET biosensors are known to be insensitive to electronic tunneling noise in the semiconductor and interference from weakly-charged proteins in physiological samples. However, their signal is still corrupted by pH fluctuations and condensing counterions in the bulk electrolyte. Here, we demonstrate that electrolyte noise is screened by the Stern layer beyond the linear Debye-Huckel limit, when the interfacial potential drop is larger than the thermal voltage. Using a fully nonlinear Gouy-Chapman-Stern (GCS) theory, a universal calibration curve is derived and shown to collapse the low-noise FET signals for miRNA, extracellular vesicles (EV), and protein, captured either directly or through silica and magnetic nanoparticle charge reporters, over eleven decades of analyte concentration. The theory involves the dissociation constant KD and a gain parameter {chi}, which represents the competing effects of the reporter charge and buffer Debye screening that must be large to produce the low-noise GCS condition. The limit of detection (LOD) is shown to be KD/{chi}, which can be optimized by varying the probe density, charge reporter, and buffer solution. An optimized hybridization buffer then yields {chi} ~ 22 (LOD ~1 pM) for miRNA detection, and multivalent capture reduces KD by four orders of magnitude for EV detection (relative to protein detection) with {chi} ~ 34 (LOD ~10 fM).

Carbon is a versatile electrode material that is used in applications ranging from electrical energy storage and electrosynthesis to CO2 conversion, H2 production, and biosensing. The development of pyrolytic carbon electrodes derived from lithographically patterned photoresist structures has expanded the possibilities for creating diverse 2D and 3D electrode designs. In this paper, we present disc-shaped SU-8-derived pyrolytic carbon scaffold electrodes with an open hexagonal honeycomb lattice. The scaffolds were fabricated, using embedded 3D printing within a shear-thinning support bath composed of fused silica nanoparticles (7% w/v) in mineral oil. The rheological properties of the support bath were optimized to enable the printing of low-viscosity materials like SU-8, which would otherwise lack structural integrity in standard extrusion-based 3D printing. The SU-8 scaffolds were then pyrolyzed and characterized using SEM, Raman spectroscopy, Energy Dispersive X-ray, X-ray Photoelectron Spectrometry, and Transmission Electron Microscopy, which revealed graphene-like 'microflowers' on its surface. Electrochemical analysis demonstrated excellent electrochemical properties. The functionality of the scaffold electrodes was validated by differentiation of human neural stem cells into dopaminergic neurons on the scaffold surface, followed by real-time detection of dopamine exocytosis upon cell depolarization.

Extracellular L-lactate reports cellular metabolism, but resolving its dynamics alongside intracellular metabolism and neuronal activity remains challenging. Here we develop eLACCO3 and R-eLACCO3, green and red cell-surface lactate biosensors with Ca2+-independent responses and faster response and recovery kinetics in cultured cells. Selected variants provide larger fluorescence responses than their predecessors in brain cells, slices, and living mice and improve detection of glucose-evoked extracellular lactate oscillations. Combining R-eLACCO3 with GCaMP6f enabled imaging of extracellular L-lactate simultaneously with odor-evoked activity in anesthetized mice and cortical activity in awake mice. These biosensors enable multiplexed measurements of extracellular lactate dynamics in relation to intracellular metabolism and neuronal activity.

At-home sampling can address obstacles to participation in transcriptomics research. We previously developed the homeRNA and homeRNAmax platforms; these custom-designed tubes containing RNA stabilizer interface with a blood tube compatible with upper-arm blood collection devices, allowing for blood collection and RNA stabilization to occur from a participant's home. In this work we introduce homeRNAdrop, an insert for a commercially available blood tube (BD Microtainer) that divides the tube into two compartments: the top compartment holds 200 L blood and the bottom compartment holds ~590 L liquid stabilizer (RNAlater). By combining blood collection and RNA stabilization into the same tube, homeRNAdrop streamlines sample preparation for participants and allows for more compact sample storage for the lab. In a remote pilot study, n=25 participants from across the United States tested the homeRNAdrop kit. The n=23 samples successfully received by the lab show that samples collected using homeRNAdrop are of sufficient RNA quality (all RINs > 6, a common cutoff for analysis) and yield (mean yield=1.44 g) for downstream gene expression analysis. Almost all participants who successfully collected blood using the Tasso Mini device found the homeRNAdrop device easy to use (n=23/24). Overall, this work adds a simplified, user-friendly platform to the growing suite of tools for remote blood RNA stabilization.

Point-of-care (POC) molecular detection has enabled rapid and accessible testing at or near the site of need, facilitating timely decision-making in clinical, field, and industrial settings. Despite these advancements, molecular detection platforms remain limited in their ability to prepare DNA from complex tissue matrices, restricting their applicability to a narrow range of sample types. To address sample preparation inefficiencies, focused ultrasound extraction (FUSE) has been developed for the rapid release of DNA from robust tissue matrices. FUSE disintegrates target tissue and releases DNA by delivering high pressure ultrasound pulses that generate a cavitation bubble cloud. In prior work, FUSE was performed using large, laboratory-based equipment. Here, a miniaturized FUSE device was designed and tested to enable POC DNA sample preparation. Design constraints were defined based on prior FUSE experiments, and based on these metrics, a 750 kHz cylindrical transducer was fabricated. The pressure output was measured, and high-speed optical imaging demonstrated that the transducer generated sustained cavitation within the defined focal region. The feasibility of DNA extraction from piscine and timber tissues was evaluated, and results show that the device can release DNA with quality suitable for PCR-based detection from both tissue types. These results demonstrate the potential of this device to rapidly extract DNA from complex samples and expand the applicability of molecular detection platforms.

Electrochemical aptamer-based (EAB) sensors have emerged as a promising framework for reagentless, real-time molecular monitoring in complex biological matrices. Signal transduction in a prominent benchmark system--targeting aminoglycoside antibiotics--has been nearly universally attributed to target-specific, binding-induced conformational changes that modulate the distance between a redox reporter and the electrode surface. Here, using a suite of interfacial electrochemical and optical characterization methods, we systematically show that charge-screening, not structure switching, dominates the signaling mechanism in the case of the aminoglycoside EAB sensor. First, we demonstrate that the legacy aminoglycoside sensor sequence exhibits apparent affinities and relative electron kinetic modulations similar to unrelated control sequences, including generic stem-loop hairpins, unstructured poly-T sequences, and short duplexes. Multi-modal validation via bio-layer interferometry (BLI), circular dichroism (CD), and fluorescence spectroscopy confirms that this promiscuous target association occurs across disparate DNA sequences and without detectable conformational reconfiguration. Further investigation via charge-scaling polyamine assays and on-electrode fluorescence imaging demonstrate that the dominant signal transduction mechanism in these sensors is instead driven by macro-scale electrostatic backbone charge-screening.

In the enzymatic toolbox of depollution, hydrolytic dehalogenases are of particular interest for the bioremediation of organohalogenated compounds. To better identify and characterize these enzymes, it is important to develop appropriate sensing methods. Fluorescent probes for dehalogenase detection have been developed in the past years, however, to this date none were available for application using the common FITC parameters (i.e. excitation laser at 488 nm). To address this limitation, we herein report a new fluorescent probe, COU4-Cl, excitable in the violet (405 nm) and blue (488 nm) wavelengths adapted for the detection and characterization of haloalkane dehalogenases. Its applicability is discussed and evaluated in comparison to the previously described COU2-Cl probe only excitable in the violet (405 nm). This study shows the advantages and complementarity of the two probes, and further demonstrate their application for the discrimination of dehalogenase activity in whole cell assays.

In vitro-transcribed (IVT) messenger RNA (mRNA) therapeutics require rigorous quality control of 5' capping efficiency and 3' poly(A) tail length, both of which constitute critical quality attributes (CQAs). Current analytical workflows for these CQAs rely on hybridization with nucleic acid probes and biotin-based affinity purification, which constrain throughput and increase per-assay cost. Here, we report a rationally designed 5' untranslated region (5' UTR) that sustains high translational efficiency while enabling probe-free, one-step purification for rapid quantification of capping efficiency and poly(A) tail length distribution. This approach exploits a strategically engineered 5' UTR incorporating a purine-only RNase A-resistant fragment terminating at a single pyrimidine cleavage site, together with a translation-enhancing element comprising an N6-methyladenosine (m6A) deposition motif and an 18S rRNA complementarity sequence. This dual-function design accommodates GA-rich sequence segments without compromising mRNA translational output. Compared with conventional probe- and biotin-dependent workflows, the present method substantially reduces cost and processing time and is compatible with simultaneous detection of segmented AmGn poly(A) tail variants. This integrated platform provides a simplified, probe-free and construct-universal for high-throughput in-process control (IPC) of mRNA therapeutics.

Raman spectroscopy (RS) has been shown to differentiate various disease states in tissue samples, yet the impact of sample substrate on spectral quality and downstream machine-learning (ML) performance is under-explored. We collected 960 spectra from 36 formalin-fixed, paraffin-embedded colonic specimens mounted in parallel on calcium fluoride (CaF2) and mirrored stainless-steel (SS) slides. Raw SS spectra were more intense than CaF2, and routine dewaxing left prominent paraffin peaks on CaF2 that were largely absent on SS. Extending CaF2 xylene immersion to 48 h reduced key paraffin peaks by 11 to 23%, aligning its biochemical profile with SS. Nested cross-validated classifiers were built to distinguish true disease (T1) from epithelial misplacement (EM). The highest accuracies were observed on SS (0.65 - 0.66), while CaF2 improved from 0.41 - 0.57 to 0.65 - 0.69 after extended dewaxing, chiefly via gains in recall. Although optimal dewaxing renders CaF2 diagnostically non-inferior, SS still offers superior accuracy, faster preparation, at approximately 4% of the cost, supporting its integration into scalable, AI-enabled RS pathology workflows.

Measuring the precise dynamics of specific neuromodulators in neurons is key to understanding how information is transmitted and processed in the brain. Despite the growing use of intensity-based neural activity sensors such as dLight in recent years, it remains challenging to monitor the dynamics of multiple neurochemicals simultaneously in live neurons. Unlike intensiometric sensors that are susceptible to artifacts caused by fluctuations in excitation power and rapid photobleaching, fluorescence lifetime-based sensors are less affected by these factors and can provide more stable measurements. Here we introduce dHaloLife635, a novel genetically encoded fluorescence-lifetime-based dopamine (DA) sensor that exhibits a fluorescence lifetime change up to -0.20 ns upon dopamine binding. dHaloLife635 consists of a G protein-coupled dopamine receptor (DRD1), a circularly permuted HaloTag (cpHaloTag), and a cell-permeable dye JF635 functionalized with a HaloTag ligand, a reactive chloroalkane linker (JF635-HTL). When dopamine binds to the dHaloLife635 sensor, it induces a conformational change in the cpHaloTag that alters the local environment of the conjugated dye, thereby changing its fluorescence lifetime. In live HEK293T cells and primary neurons, dHaloLife635 responds selectively to dopamine but not to serotonin, L-DOPA, or GABA, demonstrating excellent specificity. This dHaloLife635 sensor represents an initial step toward the establishment of a broader family of chemigenetic lifetime sensors that exhibit distinct fluorescence lifetime signatures upon binding their respective targets, thereby enabling highly specific and sensitive, real-time monitoring of multiple neurochemical dynamics in vivo.

Significance: Fluorescence imaging remains largely qualitative and device-specific, limiting reproducibility and intersystem comparisons. SI-traceable radiometric characterization requires calibrated sources suitable for transferring known radiance to imaging systems. Aim: Establish and evaluate a compact, calibrated solid-state radiometric emitter target (RET) for SI-traceable radiance transfer, and assess methods for evaluating radiance invariance, imager responsivity, and extension of radiance transfer to digitally defined regions of interest (ROIs). Approach: The radiance invariance of an LED-based RET was evaluated by measuring its radiance across varying source-to-aperture distances and collection apertures. A previously described radiance-transfer formalism based on calibrated source radiance and collection geometry was implemented to determine imager responsivity (R{lambda}), which was evaluated across varying working distances and lens apertures. Grubbs and MAD outlier tests and one-way ANOVA were used to assess radiance and responsivity invariance. Finally, responsivity obtained using digitally defined ROIs was compared with matched physical apertures to assess ROI-based radiance transfer. Results: The measured RET radiance remained invariant across the tested source-to-aperture distances and collection apertures, with no significant differences observed across distance (p = 0.88) or aperture (p = 0.15). Imager responsivity remained stable across working distances for both tested lens configurations (p = 0.48 and p > 0.99). Responsivity was also invariant across lens apertures, except for deviations at f/11 that were consistent with practical aperture tolerances. Digitally defined ROIs reproduced responsivity values obtained using matched physical apertures, demonstrating that the radiance-transfer approach can be extended to image-defined regions. Conclusions: The presented methods provide an approach for evaluating compact LED-based sources for invariant-radiance emission and suitability for SI-traceable radiance transfer. The characterized RET supported stable imager responsivity across changes in imaging geometry and extension to digitally defined ROIs. These methods can be adapted to other LED-based sources, with further angular characterization and uncertainty analysis needed to establish broader applicability.