David Issadore

Spatial manipulation of flow gradients and chemical microenvironments is essential for understanding fundamental biological mechanisms and investigating therapeutic responses in adherent cells. Convection-dominated gradient generators in microfluidic devices enable tunable chemical and shear stress gradients across large cell culture areas. However, most concentration generators are irreversibly sealed and operate in a narrow range of shear stresses, which restricts access to the cells after treatment and the physiological relevance of the flow conditions. Here, we present a reversibly sealable microfluidic platform that enables spatiotemporally controlled delivery of multiple small molecules to mammalian cells grown on large glass coverslips. Our device generates a relatively wide range of shear stresses and robust, spatially predictable chemical gradients across centimeter-scale areas and provides optical access compatible with live-cell imaging; it operates in the Stokes and laminar flow regimes. A mechanical sandwich clamp enables leak-free perfusion into the cell culture chamber and access to the cells after treatment. We experimentally and numerically demonstrate the ability to modulate the amount of mixing between co-flowing streams of small molecules. We verify the uptake of fluorophores across a monolayer of cells and assess their viability after perfusion and removal from the device. This platform provides a versatile and reusable approach for studying cellular responses to microenvironmental gradients in varied physiologically relevant shear stress conditions.

Non-viral nanomedicines, including nanoparticles (NPs) composed of lipids and polymers, represent a transformative approach to drug and gene therapy. However, clinical translation of these technologies is limited by two key barriers: the scale-up of NP formulations and the challenge of conducting predictive preclinical studies in relevant animal models. Efficient upscaling of nanomedicines, from cost and material requirement perspectives, requires manufacturing processes that can reliably provide products across the many orders of magnitude of scale from discovery (<mg of product) to large-scale testing (>kg of product). Additionally, initial preclinical studies are often performed in mouse models for discovery; however, mid- to large-size animal models such as rabbits, pigs, sheep, and nonhuman primates are more relevant to human scale and physiology in the context of evaluating the safety, efficiency, and efficacy of therapeutic strategies proposed for use in humans across age groups. This review summarizes some current strategies to scale-up the production of nanomedicines for translational investigations. Animal models and new approach methodologies are also addressed for NP assessment and screening, including the physiological distinctions when comparing rodent models to larger species that can impact NP delivery. Current challenges are also highlighted in terms of scale-up and preclinical validation with the objective of highlighting scalable, effective nanomedicine platforms that can be considered for translation to human trials.

ABSTRACT Electronic devices made from two‐dimensional materials (2DMs) significantly outperform their silicon counterparts; however, silicon CMOS technology remains commercially predominant as it offers the capability to operate dense arrays of devices in a scalable fashion. In particular, graphene Hall sensors (GHSs) offer great improvements in magnetic field sensitivity and resolution compared to silicon Hall‐effect sensors, making them extremely appealing for magnetic field imaging and biosensing. At present, GHS arrays have limited scalability compared to silicon CMOS since they require planar routing for biasing and multiplexing. In this work, we explore strategies to realize high‐density graphene Hall sensor arrays by vertically connecting GHSs with silicon CMOS biasing and multiplexing circuitry, allowing the routing and circuitry to scale with the array. We investigate the importance of design choices in the chip layout and post‐fabrication process in maximizing the reliability of graphene integration onto mm‐scale CMOS dies. Using this integration process, we show that GHSs and CMOS circuits can be monolithically integrated with high yield, creating high‐density magnetic sensing arrays with vertical biasing and readout connections. We expect that these results will lead to further improvements in magnetic sensing technology and broader advancements in large‐scale heterogeneous 2DM‐CMOS systems.

ABSTRACT Electronic devices made from two‐dimensional materials (2DMs) significantly outperform their silicon counterparts; however, silicon CMOS technology remains commercially predominant as it offers the capability to operate dense arrays of devices in a scalable fashion. In particular, graphene Hall sensors (GHSs) offer great improvements in magnetic field sensitivity and resolution compared to silicon Hall‐effect sensors, making them extremely appealing for magnetic field imaging and biosensing. At present, GHS arrays have limited scalability compared to silicon CMOS since they require planar routing for biasing and multiplexing. In this work, we explore strategies to realize high‐density graphene Hall sensor arrays by vertically connecting GHSs with silicon CMOS biasing and multiplexing circuitry, allowing the routing and circuitry to scale with the array. We investigate the importance of design choices in the chip layout and post‐fabrication process in maximizing the reliability of graphene integration onto mm‐scale CMOS dies. Using this integration process, we show that GHSs and CMOS circuits can be monolithically integrated with high yield, creating high‐density magnetic sensing arrays with vertical biasing and readout connections. We expect that these results will lead to further improvements in magnetic sensing technology and broader advancements in large‐scale heterogeneous 2DM‐CMOS systems.

Identifying plasma-based biomarkers that can accurately differentiate Lewy body disease (LBD) from Alzheimer's disease (AD) remains a major challenge. Extracellular vesicles (EVs), which carry molecular cargo from their parent cells and can cross the blood-brain barrier, offer a new path forward. We developed the multiplexed Track-Etch magnetic NanoPOre (mTENPO) platform, a highly parallelized microfluidic technology for cell-specific EV isolation, and demonstrated independent enrichment of GluR2+ (neuron-derived) and GLAST+ (astrocyte-derived) EVs from the antemortem plasma of 137 autopsy-confirmed LBD, AD, mixed pathology, and control subjects. By integrating miRNA sequencing of GluR2+ and GLAST + EV cargo with plasma measurements of Aβ40, Aβ42, tau, p-Tau181, and p-Tau231, we identified a multimodal 15-feature panel that more comprehensively reflects brain pathology than conventional biomarkers. Using tenfold cross-validation to mitigate overfitting, the panel achieved an accuracy of 0.95 and an area under the curve of 0.96 for distinguishing LBD versus AD.

Identifying plasma-based biomarkers that can accurately differentiate Lewy body disease (LBD) from Alzheimer’s disease (AD) remains a major challenge. Extracellular vesicles (EVs), which carry molecular cargo from their parent cells and can cross the blood-brain barrier, offer a new path forward. We developed the multiplexed Track-Etch magnetic NanoPOre (mTENPO) platform, a highly parallelized microfluidic technology for cell-specific EV isolation, and demonstrated independent enrichment of GluR2+ (neuron-derived) and GLAST+ (astrocyte-derived) EVs from the antemortem plasma of 137 autopsy-confirmed LBD, AD, mixed pathology, and control subjects. By integrating miRNA sequencing of GluR2+ and GLAST+ EV cargo with plasma measurements of Aβ40, Aβ42, tau, p-Tau181, and p-Tau231, we identified a multimodal 15-feature panel that more comprehensively reflects brain pathology than conventional biomarkers. Using 10-fold cross-validation to mitigate overfitting, the panel achieved an accuracy of 0.95 and an area under the curve of 0.96 for distinguishing LBD versus AD.

Ultrasmall inorganic nanoparticles (sub-5 nm) have unique biomedical advantages due to rapid clearance, enhanced imaging contrast, and potent therapeutic properties. However, current synthesis methods are limited by low throughput, polydispersity, and reliance on harsh conditions such as organic solvents or high temperatures. We report a scalable, single-step aqueous synthesis using a confined impinging jet mixer (CIJM) that produces size-controlled, clinically relevant nanoparticles, including silver sulfide, silver telluride, cerium oxide, and iron oxide, under ambient conditions. The resulting nanoparticles are homogeneous, stable, and preserve their functional biological properties. We demonstrate consistent performance across scales, establishing the CIJM as a versatile and reproducible method for producing ultrasmall inorganic nanoparticles suitable for clinical translation and high-throughput biomedical applications.

Lipid nanoparticles (LNPs) are being developed for a broad set of therapeutic applications by changing both the structures of the lipids used to formulate each LNP and their relative proportions. Because lipid synthesis and in vivo screening have been parallelized using combinatorial chemistry and LNP barcoding, respectively, the manual and sequential microfluidic formulation of LNPs remains the primary rate-limiting step during early-stage discovery. In this work, we present a parallelized, automated microfluidic platform capable of generating large, precisely defined LNP libraries in parallel, with throughput on the order of 1000 distinct formulations per hour. Each formulation is defined by varying the reagent flow ratios into one of eight microscale mixers using lithographically encoded fluidic resistors and dynamically controlled external pressure supplies. The microfluidic chip is integrated with custom robotic plate handling for the rapid collection of each distinct formulation. To evaluate this platform, we characterized 96 formulations generated on-chip in terms of both physicochemical properties and transfection efficiency in vitro. We further validated our lead candidate against the state of the art in vivo. We demonstrate the ability to rapidly discover a formulation and scale its production to liters per hour under identical mixing conditions, bridging from early discovery to manufacturing through microfluidic parallelization.

Ultrasmall inorganic nanoparticles (sub-5 nm) have unique biomedical advantages due to rapid clearance, enhanced imaging contrast, and potent therapeutic properties. However, current synthesis methods are limited by low throughput, polydispersity, and reliance on harsh conditions such as organic solvents or high temperatures. We report a scalable, single-step aqueous synthesis using a confined impinging jet mixer (CIJM) that produces size-controlled, clinically relevant nanoparticles, including silver sulfide, silver telluride, cerium oxide, and iron oxide, under ambient conditions. The resulting nanoparticles are homogeneous, stable, and preserve their functional biological properties. We demonstrate consistent performance across scales, establishing the CIJM as a versatile and reproducible method for producing ultrasmall inorganic nanoparticles suitable for clinical translation and high-throughput biomedical applications.

Granular hydrogels are emerging as an important class of scaffolds for biomedical applications, due to their injectability and pore structure to support cellular infiltration. Past research has primarily focused on spherical microgels, which allows limited control over granular hydrogel pore size and void volume fraction; however, investigation into microgels with higher aspect ratios has allowed even higher porosity. This study explores the impact of hyaluronic acid microgel aspect ratio (ranging from 3 to 5) on granular hydrogel porosity and cellular interactions. Both simulations and experimental results show increased void volume fractions and pore sizes in granular hydrogels formed from rod-like microgels when compared to volume-matched spherical microgels, which results in increased cellular invasion with an endothelial cell spheroid migration assay. Injection of the hydrogels into a confined space alters particle packing and void space, but porosity is still higher when rod-like microgels are used, which results in increased cellular invasion when injected subcutaneously. Finally, the highest aspect ratio microgels are used as injectable granular hydrogels to treat myocardial infarction in rats and show reduced infarct area and enhanced functional outcomes when compared to untreated controls. This work provides further insight into microgel shape considerations for engineered granular hydrogels.

Extracellular vesicles (EVs) play a crucial role in intercellular communication, signaling pathways, and disease pathogenesis by transporting biomolecules such as DNA, RNA, proteins, and lipids derived from their cells of origin, and they have demonstrated substantial potential in clinical applications. Their clinical significance underscores the need for sensitive methods to fully harness their diagnostic potential. In this comprehensive review, we explore EV heterogeneity related to biogenesis, structure, content, origin, sample type, and function roles; the use of EVs as disease biomarkers; and the evolving landscape of EV measurement for clinical diagnostics, highlighting the progression from bulk measurement to single vesicle analysis. This review covers emerging technologies such as single-particle tracking microscopy, single-vesicle RNA sequencing, and various nanopore-, nanoplasmonic-, immuno-digital droplet-, microfluidic-, and nanomaterial-based techniques. Unlike traditional bulk analysis methods, these methods contribute uniquely to EV characterization. Techniques like droplet-based single EV-counting enzyme-linked immunosorbent assays (ELISA), proximity-dependent barcoding assays, and surface-enhanced Raman spectroscopy further enhance our ability to precisely identify biomarkers, detect diseases earlier, and significantly improve clinical outcomes. These innovations provide access to intricate molecular details that expand our understanding of EV composition, with profound diagnostic implications. This review also examines key research challenges in the field, including the complexities of sample analysis, technique sensitivity and specificity, the level of detail provided by analytical methods, and practical applications, and we identify directions for future research. This review underscores the value of advanced EV analysis methods, which contribute to deep insights into EV-mediated pathological diversity and enhanced clinical diagnostics.

INTRODUCTION: Robust plasma-based biomarkers to distinguish Lewy body disease (LBD) and Alzheimer's disease (AD) are currently lacking. We applied track-etch magnetic nanopore (TENPO) sorting for enrichment of brain-derived extracellular vesicle (EV) signatures as potential biomarkers to address this gap. METHODS: We analyzed plasma from 137 autopsy-confirmed patients [30 LBD, 31 AD, 30 AD/LBD, 19 AD with amygdala Lewy bodies (AD/ALB), and 27 controls], sequencing miRNAs from TENPO-isolated GluR2-positive (neuron-enriched) and GLAST-positive (astrocyte-enriched) EVs, and measuring plasma proteins (Aβ40, Aβ42, tau, p-Tau181, p-Tau231) via SIMOA. RESULTS: value < .1) between LBD and AD. A multimodal 15-feature panel classified LBD versus AD with 10-fold crossvalidated accuracy = 0.95 and area under the curve (AUC) = 0.96. DISCUSSION: Brain-derived EVs offer accurate and accessible miRNA biomarkers for the differential diagnosis of LBD and AD.

Abstract Building on the success of lipid nanoparticles (LNPs) in vaccines, LNPs are being developed for a broad set of therapeutic applications by changing both the structures of the lipids used to formulate each LNP and their relative proportions. Because lipid synthesis and in vivo screening have been parallelized using combinatorial chemistry and LNP barcoding respectively, the manual and sequential microfluidic formulation of LNPs has become the rate-limiting step in the discovery process. In this work, we present a high-throughput, automated microfluidic platform capable of generating large, precisely-defined LNP libraries in parallel at a rate of one distinct formulation every three seconds. Each formulation is defined by varying the reagent flow ratios into one of eight microscale mixers using litho-graphically encoded fluidic resistors and dynamically controlled external pressure supplies. The microfluidic chip is integrated with custom frobotic plate handling for the rapid collection of each distinct formulation. Using this platform, we produce a library of 96 formulations, which we profile physicochemically and evaluate in terms of both in vitro and in vivo transfection.

BACKGROUND: Mammography screening has improved early breast cancer detection, leading to reduced mortality and lower rates of advanced breast cancer. However, mammography has a high false positive rate that results in over a million invasive breast biopsies of benign lesions in the US each year. Therefore, there is a need for noninvasive, blood-based diagnostics that can accurately assess risk of malignancy for women with indeterminate lesions identified by mammography, such as BI-RADS category 4 breast lesions. The aim of this study is to identify biomarkers from multiplexed extracellular vesicle liquid biopsy that can accurately classify mammographically detected BI-RADS 4 lesions. METHODS: We analyzed plasma from 113 prospectively enrolled subjects with BI-RADS 4 breast lesions, including 86 women with benign lesions and 27 women with malignant lesions (including 12 with stage I invasive carcinoma and 14 with ductal carcinoma in situ). None of the invasive carcinomas were metastatic. From each plasma sample, we used track etched magnetic nanopore technology to separately isolate HER2 and CD24 expressing extracellular vesicles (EVs) and measured their miRNA cargo using next-generation sequencing. We evaluated the performance of EV-miRNA biomarkers for classifying malignancy and applied LASSO classification to identify a panel of four complementary EV miRNA biomarkers that we validated by qPCR. RESULTS: We identified 19 differentially enriched miRNA from HER2+ EVs and 11 differentially enriched miRNA from CD24+ EVs of women with malignant lesions compared to benign lesions. We observed individual miRNA with an AUC of up to 0.87 for miR-340-5p from HER2+ EVs and 0.75 for miR-223-3p from CD24+ EVs. LASSO classification selected a panel of four complementary EV miRNA for classifying breast cancer: miR-340-5p (HER2+ EVs), miR-598-3p (CD24+), miR-15b-5p (HER2+), and miR-126-3p (CD24+). CONCLUSIONS: HER2+ and CD24+ EV subpopulations contain complementary biomarkers suitable for validation in larger studies that can accurately detect early-stage breast cancer among women with BI-RADS category 4 breast lesions.

Abstract Digital enzyme-linked immunoassays (dELISA) have been successfully applied to the ultrasensitive quantification of analytes, including nucleic acids, proteins, cells, and extracellular vesicles, achieving robust detection limits in complex clinical specimens such as blood, and demonstrating utility across a broad range of clinical applications. The ultrasensitivity of dELISA comes from partitioning single analytes, captured onto a microbead, into millions of compartments so that they can be counted individually. There is particular interest in using dELISA for multiplexed measurements, but generating and detecting the billions of compartments necessary to perform multiplexed ultrasensitive dELISA remains a challenge. To address this, we have developed a high-throughput, optofluidic platform that performs quantitative fluorescence measurements on five populations of microbeads, each encoded with distinct ratios of two fluorescent dyes, for digital assays. The key innovation of our work is the parallelization of droplet generation and detection, combined with time-domain encoding of the excitation sources into distinct patterns that barcode the emission signal of both dyes within each bead, achieving high throughput (6 × 10 6 droplets/min) and accurate readout. Additionally, we modulate the exposure settings of the digital camera, capturing images of multiplexed beads and the droplet fluorescent substrate in consecutive frames, a method inspired by high dynamic range (HDR) photography. Our platform accurately classifies five populations of dual-encoded beads (accuracy &gt; 99%) and detects bead-bound streptavidin-horseradish peroxidase molecules in a third fluorescence channel. This work establishes the technological foundation to combine high multiplexing and high throughput for droplet digital assays.

Microglial state at the time of concussion dictates cognitive outcomes, yet the underlying mechanisms remain unclear, and non-invasive tools to predict recovery trajectories remain elusive. Here, we tested whether microglia are causally required for concussion-induced deficits and the neuroprotection conferred by subconcussive preconditioning. Using PLX5622 to deplete microglia in a preclinical model, we observed opposing cognitive effects: depletion rescues deficits from concussion alone but eliminates preconditioning-induced protection. To characterize the molecular mechanisms underlying these divergent trajectories, we performed single-nuclei transcriptomics and isolated brain-derived (GluR1/2+) extracellular vesicles (EVs) from plasma. We found that microglial presence and subconcussive preconditioning fundamentally alter injury biomarkers and signaling pathways across multiple cell types. Furthermore, we identified a plasma EV miRNA panel that predicts cognitive recovery across varied injury conditions. Together, these results demonstrate a dual, context-dependent role for microglia in concussion outcomes and establish brain-derived EVs as a powerful tool for surveilling neuroinflammatory processes governing recovery. Teaser: Microglial state during concussion affects cognitive recovery and neuron-enriched extracellular vesicle biomarkers.

We have developed a platform for the multiplexed and ultrasensitive profiling of individual extracellular vesicles (EVs) directly in plasma, which we call GDEVA─Agarose micro G el-based D igital single-molecule–single EV A ssay. GDEVA achieves single-molecule sensitivity and moderate multiplexing (demonstrated 3-plex), and can achieve a throughput of ∼10 4 EVs per minute necessary to resolve EVs directly in human plasma when read out using flow cytometry. Our platform integrates a rolling circle amplification (RCA) immunoassay of EV surface proteins, which are cleaved from single EVs, and amplified within agarose microgels, followed by flow cytometry-based readout or imaging after fluorescence-activated cell sorting (FACS). It overcomes steric hindrance of RCA products, nonspecific binding of RCA templates, and the lack of quantitation of multiple proteins on EVs that have plagued earlier approaches. We evaluated the analytical capabilities of GDEVA through head-to-head comparison with conventional technology and demonstrated a ∼100× improvement in the limit of detection (LOD) of EV subpopulations. We evaluate GDEVA’s potential in cancer immunology, by analyzing single EVs in plasma samples from patients with melanoma, where EV heterogeneity plays a critical role in disease progression and response to therapy. We demonstrate profiling of individual EVs for key immune markers PD-L1, CD155, and the melanoma marker TYRP-1, and showed that GDEVA can precisely quantify EVs, offering the resolution to detect rare EV subpopulations in complex clinical specimens.

Lipid nanoparticles (LNPs) are the most advanced delivery system currently available for RNA therapeutics. Their development has accelerated rapidly since the success of Patisiran, the first siRNA-LNP therapeutic, and the SARS-CoV-2 mRNA vaccines that emerged during the COVID-19 pandemic. Designing LNPs with specific targeting, high potency, and minimal side effects is crucial for their successful clinical use. However, our understanding of how the composition and mixing methods influence the structure, biophysical properties, and biological activity of the resulting particles remains limited. While microfluidic technologies have significantly improved the speed and uniformity of LNP production, a major challenge that remains is that ~60-80% of mRNA-LNP formulations are unloaded (empty lipid particles). This study tackles this challenge by relating current standard characterization methods with more powerful emerging methods, including 1. multi-wavelength analytical ultracentrifugation (MWL-AUC), 2. In-line multi-angle light scattering (MALS) methods, and 3. synchrotron size-exclusion chromatography in-line with small-angle X-ray scattering (SEC-SAXS) coupled with singular-value decomposition methods (SVD). We will present the strengths and weaknesses of each approach and showcase the increased detail newer advanced methods provide by comparing LNP formulations made using two common small-scale production methods: microfluidic rapid mixing and bulk mixing. The characterization techniques employed here can enhance our understanding of LNP structure-function relationships and enable researchers to define their RNA LNP products more precisely, which can improve LNP quality and potentially accelerate pharmaceutical development.

Nanoparticles have gained attention as drug delivery vehicles for cancer treatment, but often struggle with poor tumor accumulation and penetration. Single external magnets can enhance magnetic nanoparticle delivery but are limited to superficial tumors due to the rapid decline in the magnetic field strength with distance. We previously showed that a 2-magnet device could extend targeting to greater tissue depths. Here, we improve on this approach by constructing an 8-magnet device arranged in an annular Halbach array, which facilitates radial outward movement of magnetic nanoparticles from the bore's center. Using chlorin e6-coated magnetic nanoclusters (Ce6 clusters) with densely packed cobalt-doped superparamagnetic iron oxide nanoparticles, we demonstrated nearly a 7-fold improvement in nanoparticle movement through a porous matrix compared to the 2-magnet approach. This resulted in enhanced magnetic resonance contrast, accumulation, and penetration of Ce6 clusters into 4T1 triple-negative breast tumors in mice, leading to improved photodynamic therapy and highlighting the potential therapeutic application of the 8-magnet device.

Designing lipid nanoparticle (LNP) delivery systems with specific targeting, potency and minimal side effects is crucial for their clinical use. However, traditional characterization methods, such as dynamic light scattering, cannot accurately quantify physicochemical properties of LNPs and how they are influenced by the lipid composition and mixing method. Here we structurally characterize polydisperse LNP formulations by applying emerging solution-based biophysical methods that have higher resolution and provide biophysical data beyond size and polydispersity. These techniques include sedimentation velocity analytical ultracentrifugation, field-flow fractionation followed by multi-angle light scattering, and size-exclusion chromatography in-line with synchrotron small-angle X-ray scattering. We show that LNPs have intrinsic polydispersity in size, RNA loading, and shape, which depends on both the formulation technique and lipid composition. Lastly, we predict LNP transfection in vitro and in vivo by examining the relationship between mRNA translation and physicochemical characteristics. Solution-based biophysical methods will be essential for determining LNP structure-function relationships, facilitating the creation of new design rules for LNPs.

Despite the numerous advantages demonstrated by microfluidic mixing for RNA-loaded lipid nanoparticle (RNA-LNP) production over bulk methods, such as precise size control, homogeneous distributions, higher encapsulation efficiencies, and improved reproducibility, their translation from research to commercial manufacturing remains elusive. A persistent challenge hindering the adoption of microfluidics for LNP production is the fouling of device surfaces during prolonged operation, which significantly diminishes performance and reliability. The complexity of LNP constituents, including lipids, cholesterol, RNA, and solvent mixtures, makes it difficult to find a single coating that can prevent fouling. To address this challenge, we propose using an immobilized liquid lubricant layer of perfluorodecalin (PFD) to create an antifouling surface that can repel the multiple LNP constituents. We apply this technology to a staggered herringbone microfluidic (SHM) mixing chip and achieve >3 h of stable operation, a >15× increase relative to gold standard approaches. We also demonstrate the compatibility of this approach with a parallelized microfluidic platform that incorporates 256 SHM mixers, with which we demonstrate scale up, stable production at L/h production rates suitable for commercial scale applications. We verify that the LNPs produced on our chip match both the physiochemical properties and performance for both in vitro and in vivo mRNA delivery as those made on chips without the coating. By suppressing surface fouling with an immobilized liquid lubricant layer, this technology not only enhances RNA-LNP production but also promises to transform the microfluidic manufacturing of diverse materials, ensuring more reliable and robust processes.

As they became the dominant gene therapy platform, lipid nanoparticles (LNPs) experienced nearly all their innovation in varying the structure of individual molecules in LNPs. This ignored control of the spatial arrangement of molecules, which is suboptimal because supramolecular structure determines function in biology. To control LNPs' supramolecular structure, we introduce multi-stage-mixing (MSM) to successively add different molecules to LNPs. We first utilize MSM to create a core-then-shell (CTS) synthesis. CTS-LNPs display a clear core-shell structure, vastly lower frequency of LNPs containing no detectable mRNA, and improved mRNA-LNP expression. With DNA-loaded LNPs, which for decades lagged behind mRNA-LNPs due to low expression, CTS improved DNA-LNPs' protein expression by 2-3 orders of magnitude, bringing it within range of mRNA-LNPs. These results show that supramolecular arrangement is critical to LNP performance and can be controlled by mixing methodology. Further, MSM/CTS have finally made DNA-LNPs into a practical platform for long-term gene expression.

Abstract Purpose Ultrasmall silver sulfide nanoparticles (Ag 2 S-NP) have been identified as promising contrast agents for a number of modalities and in particular for dual-energy mammography. These Ag 2 S-NP have demonstrated marked advantages over clinically available agents with the ability to generate higher contrast with high biocompatibility. However, current synthesis methods for inorganic nanoparticles are low-throughput and highly time-intensive, limiting the possibility of large animal studies or eventual clinical use of this potential imaging agent. Methods We herein report the use of a scalable silicon microfluidic system (SSMS) for the large-scale synthesis of Ag 2 S-NP. Ag 2 S-NP produced using this system were compared to bulk synthesis and a commercially available microfluidic device through characterization, contrast generation, in vivo imaging, and clearance profiles. Results Using SSMS chips with 1 channel, 10 parallelized channels, and 256 parallelized channels, we determined that the Ag 2 S-NP produced were of similar quality as measured by core size, concentration, UV–visible spectrometry, and in vitro contrast generation. Moreover, by combining parallelized chips with increasing reagent concentration, we were able to increase output by an overall factor of 5,100. We also found that in vivo imaging contrast generation was consistent across synthesis methods and confirmed renal clearance of the ultrasmall nanoparticles. Finally, we found best-in-class clearance of the Ag 2 S-NP occurred within 24 h. Conclusions These studies have identified a promising method for the large-scale production of Ag 2 S-NP, paving the way for eventual clinical translation.

orting. Unlike conventional approaches, BDEVS achieves single molecule sensitivity and moderate multiplexing (demonstrated 3-plex) without sacrificing the throughput (processing ten thousand of EVs per minute) necessary to resolve EVs directly in human plasma. Our platform integrates rolling circle amplification (RCA) of EV surface proteins, which are cleaved from single EVs, and amplified within agarose droplets, followed by flow cytometry-based readout and sorting, overcoming steric hindrance, non-specific binding, and the lack of quantitation of multiple proteins on EVs that have plagued earlier approaches. We evaluated the analytical capabilities of BDEVS through head-to-head comparison with gold-standard technologies, and demonstrated a ∼100x improvement in the limit of detection of EV subpopulations. We demonstrate the high throughput (∼100k beads / minute) profiling of individual EVs for key immune markers PD-L1, CD155, and the melanoma tumor marker TYRP-1, and showed that BDEVS can precisely quantify and sort EVs, offering unprecedented resolution for analyzing tumor-immune interactions and detecting rare EV subpopulations in complex clinical specimens. We demonstrate BDEVS's potential as a transformative tool for EV-based diagnostics and therapeutic monitoring in the context of cancer immunology by analyzing plasma samples from patients with melanoma, where EV heterogeneity plays a critical role in disease progression and response to therapy.

While understanding mitochondrial DNA (mtDNA) heteroplasmy and intercellular heterogeneity requires singlecell, single-mtDNA analysis, existing methods restrict studies to small cell populations [1,2].Water-in-oil droplet microfluidics improved the throughput of single cell analysis >100,000 cells, but it has been challenging for subcellular organelle analysis as their hierarchy in single-cell level should be resolved by multistep bioassays [3].Hydrogel droplet microfluidics has great potential for sub-cellular molecule analysis as they allow single-cell compartmentalization even after multiple times of buffer exchange steps.Here, we present a high-throughput, multiplex method for single-cell, single-mtDNA mutation analysis.(Figure 1).mtDNA from individual cells were isolated within porous structure of agarose beads after the agarose gelation and cell lysis.A microfluidic droplet generator was used to form a dense porous structure enough to retain mtDNA from a single cell, and the retention ratio of mtDNA was evaluated ~95% by a qPCR (Figure 2A,B).To mitigate the hindered throughput of agarose droplet generation due to its high viscosity, we incorporated parallelized microfluidic droplet generators which achieved throughput >70,000 drops/min (Figure 2C).mtDNA from single cells within agarose beads were analyzed by using a rolling circle amplification (RCA) (Figure 3A).RCA can localize amplified signal as a few hundred nm to a few m punctate, which are large enough to be retained in agarose bead.First, padlock probe was annealed to a specific region of mtDNA after the denaturation using 60% DMSO.Subsequently, padlock probe was ligated to form a circular DNA and primer was hybridized on the circle DNA.After RCA reaction, RCA products, large punctate were generated within agarose beads and visualized by fluorescent detection probes.Based on this method, Cross-contamination of mtDNA between beads during a sample preparation was validated by using mouse and human cells (Figure 3B).There was minimal cross-contamination by noting that agarose beads have either ATTO565 or ATTO647 fluorescence signal, which was confirmed by a flow cytometer (Figure 3C,D).Agarose beads that had encapsulated single cell was ensured by SYBR green gDNA stain.Fluorescence signal of RCA products generated from mtDNA showed significant difference between SYBR green positive and negative beads.Then we evaluated multiplex assay on single-mtDNA from single cell to analyze large area deletion by targeting D-loop and 4,977 deletion regions (Figure 4A).RCA products labelled with different fluorescence were distributed throughout a single agarose bead (Figure 4B,C).Different fluorescence profile of each bead analyzed by imaging and flow cytometry, which revealed heteroplasmy and intercellular heterogeneity of mtDNA 4,977 deletion (Figure 4D,E).Furthermore, padlock probe-based RCA assay was applied for mtDNA single nucleotide variation (SNV) analysis in single-cell level (Figure 5A).By locating SNV region at the end of padlock probe, SNV of mtDNA can be detected by RCA products labelled with different fluorescent detection probes.It was shown that more RCA products were generated from padlock probes targeting wild type in both single-plex and multiplex assay (Figure 5B).The proposed method will open a new avenue for advancing our understanding of the biological role of mtDNA heteroplasmy.

BACKGROUND: Mitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting "normal" mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes, we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes. In this study, we amplified mt-genomes from 1645 single mitochondria isolated from mouse single astrocytes and neurons to (1) determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome, (2) assess differences in mtDNA SNVs between neurons and astrocytes, and (3) study co-segregation of variants in the mouse mtDNA. RESULTS: (1) The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. (2) Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G > A and 9419:C > T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. (3) Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461. CONCLUSIONS: This study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.

Graphene Hall-effect magnetic field sensors (GHSs) exhibit high performance comparable to state-of-the-art commercial Hall sensors made from III-V semiconductors. Graphene is also amenable to CMOS-compatible fabrication processes, making GHSs attractive candidates for implementing magnetic sensor arrays for imaging fields in biosensing and scanning probe applications. However, their practical appeal is limited by response heterogeneity and drift, arising from the high sensitivity of two-dimensional (2D) materials to local device imperfections. To address this challenge, we designed a GHS array in which an individual backgate is added to each GHS, allowing the carrier density of each sensor to be electrostatically tuned independent of other sensors in the array. Compared to the constraints encountered when all devices are tuned with the same backgate, we expected that the flexibility afforded by individual tuning would allow for the array's sensitivity, uniformity, and reconfigurability to be enhanced. We fabricated an array of 16 GHSs, each with its own backgate terminal, and characterized the ability to modulate GHS carrier density and Hall sensitivity within CMOS-compatible voltage ranges. We then demonstrated that individual device tuning can be used to break the trade-off between device sensitivity and uniformity in the GHS array, allowing for enhancement of both objectives. Our results showed that GHS arrays exhibiting >30% variability under single-backgate operation could be compensated using individual tuning to achieve <2% variability with minimal impact on the array sensitivity.

Background: Mitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting 'normal' mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes In this study we amplified mt-genomes from 1,645 single mitochondria (mts) isolated from mouse single astrocytes and neurons to 1. determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome, 2. assess differences in mtDNA SNVs between neurons and astrocytes, and 3. Study cosegregation of variants in the mouse mtDNA. Results: 1. The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. 2. Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G>A and 9419:C>T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. 3. Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461. Conclusion: This study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.

There is growing interest in understanding the biological implications of single cell heterogeneity and heteroplasmy of mitochondrial DNA (mtDNA), but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi-step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95 % mtDNA retention from single cells within our microbeads at >700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single-mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

Abstract There is growing interest in understanding the biological implications of single cell heterogeneity and heteroplasmy of mitochondrial DNA (mtDNA), but current methodologies for single‐cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single‐cell genomic, RNA, and protein analysis, their application to sub‐cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose‐based droplet microfluidic approach for single‐cell, single‐mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within &gt;10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi‐step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95 % mtDNA retention from single cells within our microbeads at &gt;700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single‐mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

There is growing interest in understanding the biological implications of single cell heterogeneity and intracellular heteroplasmy of mtDNA, but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi-step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95% mtDNA retention from single cells within our microbeads at >700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

background. We achieve a 0.006% false positive rate per droplet by leveraging avidity effects that arise from EVs having multiple copies of their target ligands on their surface. We use parallelized optofluidics to rapidly process 10 million droplets per minute, ∼100× greater than conventional approaches. A validation study on a cohort of 14 patients with melanoma confirms DEVA's ability to match conventional ELISA measurements with reduced plasma sample volume and without the need for prior EV purification. This proof-of-concept study demonstrates DEVA's potential for clinical utility to enhance prognosis as well as guide treatment for cancer.

Abstract Ultrasmall silver sulfide nanoparticles (Ag 2 S-NP) have been identified as promising contrast agents for a number of modalities and in particular for dual-energy mammography. These Ag 2 S-NP have demonstrated marked advantages over clinically available agents with the ability to generate higher contrast with high biocompatibility. However, current synthesis methods are low-throughput and highly time-intensive, limiting the possibility of large animal studies or eventual clinical use of this potential imaging agent. We herein report the use of a scalable silicon microfluidic system (SSMS) for the large-scale synthesis of Ag 2 S-NP. Using SSMS chips with 1 channel, 10 parallelized channels, and 256 parallelized channels, we determined that the Ag 2 S-NP produced were of similar quality as measured by core size, concentration, UV-visible spectrometry, and in vitro contrast generation. Moreover, by combining parallelized chips with increasing reagent concentration, we were able to increase output by an overall factor of 3,400. We also found that in vivo imaging contrast generation was consistent across synthesis methods and confirmed renal clearance of the ultrasmall nanoparticles. Finally, we found best-in-class clearance of the Ag 2 S-NP occurred within 24 hours. These studies have identified a promising method for the large-scale production of Ag 2 S-NP, paving the way for eventual clinical translation.