Microfluidic Imaging Research Articles

A study on the microscopic mechanism of oil displacement in an adaptive profile control and plugging composite displacement system

This study employed a self-designed microfluidic chip with visualized oil displacement technology and indoor core flooding experiments to reveal the microscopic plugging and adjustment mechanisms. Additionally, it involved the microscopic oil displacement mechanism of an adaptive plugging and flooding composite system containing PPG (preformed particle gel) particles and two blended surfactants. The results indicated that microfluidic imaging captured the dynamic seepage characteristics of PPG particles after swelling, which involved plugging, deformation, and passage through a 0.3 mm throat in a series of pores, achieving adaptive plugging between the size of PPG particles and the pore size. The plugging mechanism of PPG particles involves blocking larger parallel pores, increasing the displacement velocity in smaller pores, and dynamically adjusting the plugging to achieve simultaneous displacement in the high- and low-permeability layers. The displacement mechanism of PPG particles in the simulated pores includes reducing seepage radius, expanding sweep area, and repeatedly overcoming capillary forces. The pressure variation data along the length of different permeability long cores demonstrated that the pressure drop within the first third of the injection end increases with an increase in permeability. The pressure change curve illustrates the migration characteristics of PPG particles in the pore throats, characterized by “accumulation and plugging–pressure increase–deformation and migration.” After injecting the adaptive plugging and flooding composite system following polymer flooding, the flow fraction in the high-permeability layers decreased to 25.65 %, whereas that in the low-permeability layers increased to 74.56 %. The difference in the water flooding pressure before and after implementing the adaptive plugging and flooding system reached a factor of 29, and the oil recovery rate improved by 5.55 % compared to a weak alkaline ternary composite system. The adaptive plugging and flooding composite system demonstrated a synergistic effect in expanding swept volume, blocking preferential flow channels, and enhancing oil displacement efficiency. It achieved the effects of simultaneous plugging and flooding, dynamic plugging adjustment, and synchronized displacement in the high- and low-permeability layers, thereby significantly improving the mobilization of residual oil after polymer flooding.

Experimental validation of a parenteral permitted daily exposure value for cleaning-induced degradants from recombinant therapeutic proteins with in vitro immunogenicity assays

Multiproduct manufacturing of biotherapeutic proteins generate cleaning-induced protein degradants because of extreme pH and temperature conditions during the cleaning process. Cleaning Acceptance limits are calculated based on the maximum allowable carryover (MAC) assessment of the previously manufactured active pharmaceutical ingredient (API) – or drug product – based on the permitted daily exposure (PDE) of the previously manufactured API into the dose of subsequent product. In this study, we tested a previously determined PDE value for cleaning-induced protein degradants of 650 µg/dose. A bench-scale cleaning method was used to generate cleaning induced degradants from both a half-life extension (HLE) BiTE® molecule and a mAb product. For this investigation degradants of HLE BiTE®-A and mAb-1 were characterized either alone or degradants of HLE BiTE®-A and mAb-1 spiked into mAb-1 at 650 µg. These samples were characterized by endotoxin testing, size exclusion chromatography (SEC), light obscuration by HIAC, and micro-fluidic imaging (MFI). These results suggest that significant degradation of the molecule occurs because of the cleaning procedure, and it is no longer in the intact form or active state. The biological impact was assessed using a cell line assay to assess immune activation, and a human Peripheral Blood Mononuclear Cell (PBMC) assay to assess T cell activation, T cell proliferation, and cytokine release after 20 h and 7 days. Findings from the various in vitro cell-based assays suggest that the presence of 650 µg of carryover of degradants either alone or spiked into the same or a cross-product do not increase immunogenicity risk in cell-based assays – suggesting that the current PDE of 650 µg/dose for cleaning-induced degradant carryover does not have a risk of immunogenicity in patients.

A Preliminary Analysis of Circulating Tumor Microemboli from Breast Cancer Patients during Follow-Up Visits.

Most breast cancer-related deaths are caused by distant metastases and drug resistance. It is important to find appropriate biomarkers to monitor the disease and to predict patient responses after treatment early and accurately. Many studies have found that clustered circulating tumor cells, with more correlations with metastatic cancer and poor survival of patients than individual ones, are promising biomarkers. Eighty samples from eleven patients with breast cancer during follow-up visits were examined. By using a microfluidic chip and imaging system, the number of circulating tumor cells and microemboli (CTC/CTM) were counted to assess the distribution in stratified patients and the potential in predicting the disease condition of patients after treatments during follow-up visits. Specific components and subtypes of CTM were also preliminarily investigated. Compared to CTC, CTM displayed a distinguishable distribution in stratified patients, having a better AUC value, in predicting the disease progression of breast cancer patients during follow-up visits in this study. Four subtypes were categorized from the identified CTM by considering different components. In combination with CEA and CA153, enumerated CTC and CTM from individual patients were applied to monitor the disease condition and patient response to the therapy during follow-up visits. The CTM and its subtypes are promising biomarkers and valuable tools for studying cancer metastasis and longitudinally monitoring cancer patients during follow-up visits.

Fibronectin induces a transition from amoeboid to a fan morphology and modifies migration in Entamoeba histolytica.

Cell migration modes can vary, depending on a number of environmental and intracellular factors. The high motility of the pathogenic amoeba Entamoeba histolytica is a decisive factor in its ability to cross the human colonic barrier. We used quantitative live imaging techniques to study the migration of this parasite on fibronectin, a key tissue component. Entamoeba histolytica amoebae on fibronectin contain abundant podosome-like structures. By using a laminar flow chamber, we determined that the adhesion forces generated on fibronectin were twice those on non-coated glass. When migrating on fibronectin, elongated amoeboid cells converted into fan-shaped cells characterized by the presence of a dorsal column of F-actin and a broad cytoplasmic extension at the front. The fan shape depended on the Arp2/3 complex, and the amoebae moved laterally and more slowly. Intracellular measurements of physical variables related to fluid dynamics revealed that cytoplasmic pressure gradients were weaker within fan-shaped cells; hence, actomyosin motors might be less involved in driving the cell body forward. We also found that the Rho-associated coiled-coil containing protein kinase regulated podosome dynamics. We conclude that E. histolytica spontaneously changes its migration mode as a function of the substrate composition. This adaptive ability might favour E. histolytica's invasion of human colonic tissue. By combining microfluidic experiments, mechanical modelling, and image analysis, our work also introduces a computational pipeline for the study of cell migration.

Integration of wide-field imaging system with droplet microfluidics for monitoring living bacteria

Droplet microfluidics has been widely used to analyze chemicals and biological reactions at the single-molecule level. Microscopic systems are commonly used for imaging and analyzing droplets using high-magnification objective lenses. However, these systems are expensive, complex, and large, limiting the high-throughput characterization of droplets in reactions targeting disease-related biomarkers, including nucleic acids, proteins, and pathogens. Another concern is the time gap between droplet analysis within a microfluidic channel and imaging chamber, which can cause discrepancies in reaction time between droplets. To address this issue, we introduce the droplet analysis system for vast imaging and statistical tool (DropVIST)—a wide-field imaging system integrated with droplet microfluidics for rapid and accurate droplet analysis. DropVIST can detect eight differently colored droplets simultaneously using a wide-field imaging system and dFinder software, which can quantify the reacted droplets. The smallest droplet diameter for detection was 30 μm, and the maximum detection area was 201.84 cm2, suggesting that the system can theoretically analyze 3103,377 droplets in real-time. We validated the monitoring performance of DropVIST using clinical isolates of five types of living pathogenic bacteria and compared this with conventional approaches, including the microbroth dilution method and colony-forming unit assay. This platform provides a rapid, simple, and accurate tool for monitoring living bacteria at the single-cell level.

Assessment of Red Blood Cell Aggregation in Preeclampsia by Microfluidic Image Flow Analysis-Impact of Oxidative Stress on Disease Severity.

Preeclampsia (PE) is a hypertensive disease characterized by proteinuria, endothelial dysfunction, and placental hypoxia. Reduced placental blood flow causes changes in red blood cell (RBC) rheological characteristics. Herein, we used microfluidics techniques and new image flow analysis to evaluate RBC aggregation in preeclamptic and normotensive pregnant women. The results demonstrate that RBC aggregation depends on the disease severity and was higher in patients with preterm birth and low birth weight. The RBC aggregation indices (EAI) at low shear rates were higher for non-severe (0.107 ± 0.01) and severe PE (0.149 ± 0.05) versus controls (0.085 ± 0.01; p < 0.05). The significantly more undispersed RBC aggregates were found at high shear rates for non-severe (18.1 ± 5.5) and severe PE (25.7 ± 5.8) versus controls (14.4 ± 4.1; p < 0.05). The model experiment with in-vitro-induced oxidative stress in RBCs demonstrated that the elevated aggregation in PE RBCs can be partially due to the effect of oxidation. The results revealed that RBCs from PE patients become significantly more adhesive, forming large, branched aggregates at a low shear rate. Significantly more undispersed RBC aggregates at high shear rates indicate the formation of stable RBC clusters, drastically more pronounced in patients with severe PE. Our findings demonstrate that altered RBC aggregation contributes to preeclampsia severity.

Natural Disinfection-like Process Unveiled in Soil Microenvironments by Enzyme-Catalyzed Chlorination.

Substantial natural chlorination processes are a growing concern in diverse terrestrial ecosystems, occurring through abiotic redox reactions or biological enzymatic reactions. Among these, exoenzymatically mediated chlorination is suggested to be an important pathway for producing organochlorines and converting chloride ions (Cl-) to reactive chlorine species (RCS) in the presence of reactive oxygen species like hydrogen peroxide (H2O2). However, the role of natural enzymatic chlorination in antibacterial activity occurring in soil microenvironments remains unexplored. Here, we conceptualized that heme-containing chloroperoxidase (CPO)-catalyzed chlorination functions as a naturally occurring disinfection process in soils. Combining antimicrobial experiments and microfluidic chip-based fluorescence imaging, we showed that the enzymatic chlorination process exhibited significantly enhanced antibacterial activity against Escherichia coli and Bacillus subtilis compared to H2O2. This enhancement was primarily attributed to in situ-formed RCS. Based on semiquantitative imaging of RCS distribution using a fluorescence probe, the effective distance of this antibacterial effect was estimated to be approximately 2 mm. Ultrahigh-resolution mass spectrometry analysis showed over 97% similarity between chlorine-containing formulas from CPO-catalyzed chlorination and abiotic chlorination (by sodium hypochlorite) of model dissolved organic matter, indicating a natural source of disinfection byproduct analogues. Our findings unveil a novel natural disinfection process in soils mediated by indigenous enzymes, which effectively links chlorine-carbon interactions and reactive species dynamics.

Embedded Blur-Free Single-Image Acquisition Pipeline for Droplet Microfluidic Imaging Flow Cytometry (IFC)

Embedded Blur-Free Single-Image Acquisition Pipeline for Droplet Microfluidic Imaging Flow Cytometry (IFC)

Robotic microfluidic imaging of blood stimulation- towards high-throughput portable measurement of haemostasis

Measuringblood and platelet function is vital for the development and use of drugs thatcombat cardiovascular disease, such as anti-platelet drugs and other medicinesthat reduce the risk of thrombosis. We propose combining mass-produced microfluidicdevices with open-source robotic instrumentation to enable development of affordableand portable, yet high-throughput and high-performance haematological testing.A time- and distance-resolved fluid flow analysis by Raspberry Pi imagingintegrated with controlled sample addition and illumination, enablessimultaneous tracking of capillary rise in 120 individual capillaries within 5minutes. We showed that time-resolved microcapillary rise imaging permits bloodfunction measurement by measuring thrombin-triggered activation of globalhaemostasis. Thrombin stimulation slowed vertical fluid velocity, consistentwith a dynamic increase in viscosity. Microfluidic systems expandhaematological testing towards high-efficiency, multi-parameter blood analysisnecessary for understanding and improving cardiovascular health.

Microfluidic reactor designed for time-lapsed imaging of pretreatment and enzymatic hydrolysis of lignocellulosic biomass

The effect of tissue-specific biochemical heterogeneities of lignocellulosic biomass on biomass deconstruction is best understood through confocal laser scanning microscopy (CLSM) combined with immunohistochemistry. However, this process can be challenging, given the fragility of plant materials, and is generally not able to observe changes in the same section of biomass during both pretreatment and enzymatic hydrolysis. To overcome this challenge, a custom polydimethylsiloxane (PDMS) microfluidic imaging reactor was constructed using standard photolithographic techniques. As proof of concept, CLSM was performed on 60 μm-thick corn stem sections during pretreatment and enzymatic hydrolysis using the imaging reactor. Based on the fluorescence images, the less lignified parenchyma cell walls were more susceptible to pretreatment than the lignin-rich vascular bundles. During enzymatic hydrolysis, the highly lignified protoxylem cell wall was the most resistant, remaining unhydrolyzed even after 48 h. Therefore, imaging thin whole biomass sections was useful to obtain tissue-specific changes during biomass deconstruction.

Enhancing Microdroplet Image Analysis with Deep Learning.

Microfluidics is a highly interdisciplinary field where the integration of deep-learning models has the potential to streamline processes and increase precision and reliability. This study investigates the use of deep-learning methods for the accurate detection and measurement of droplet diameters and the image restoration of low-resolution images. This study demonstrates that the Segment Anything Model (SAM) provides superior detection and reduced droplet diameter error measurement compared to the Circular Hough Transform, which is widely implemented and used in microfluidic imaging. SAM droplet detections prove to be more robust to image quality and microfluidic images with low contrast between the fluid phases. In addition, this work proves that a deep-learning super-resolution network MSRN-BAM can be trained on a dataset comprising of droplets in a flow-focusing microchannel to super-resolve images for scales ×2, ×4, ×6, ×8. Super-resolved images obtain comparable detection and segmentation results to those obtained using high-resolution images. Finally, the potential of deep learning in other computer vision tasks, such as denoising for microfluidic imaging, is shown. The results show that a DnCNN model can denoise effectively microfluidic images with additive Gaussian noise up to σ = 4. This study highlights the potential of employing deep-learning methods for the analysis of microfluidic images.

Microfluidics on lensless, semiconductor optical image sensors: challenges and opportunities for democratization of biosensing at the micro-and nano-scale.

Optical image sensors are 2D arrays of pixels that integrate semiconductor photodiodes and field effect transistors for efficient photon conversion and processing of generated electrons. With technological advancements and subsequent democratization of these sensors, opportunities for integration with microfluidics devices are currently explored. 2D pixel arrays of such optical image sensors can reach dimensions larger than one centimeter with a sub-micrometer pixel size, for high spatial resolution lensless imaging with large field of view, a feat that cannot be achieved with lens-based optical microscopy. Moreover, with advancements in fabrication processes, the field of microfluidics has evolved to develop microfluidic devices with an overall size below one centimeter and individual components of sub-micrometer size, such that they can now be implemented onto optical image sensors. The convergence of these fields is discussed in this article, where we review fundamental principles, opportunities, challenges, and outlook for integration, with focus on contact-mode imaging configuration. Most recent developments and applications of microfluidic lensless contact-based imaging to the field of biosensors, in particular those related to the potential for point of need applications, are also discussed.

OrganoidChip facilitates hydrogel-free immobilization for fast and blur-free imaging of organoids

Organoids are three-dimensional structures of self-assembled cell aggregates that mimic anatomical features of in vivo organs and can serve as in vitro miniaturized organ models for drug testing. The most efficient way of studying drug toxicity and efficacy requires high-resolution imaging of a large number of organoids acquired in the least amount of time. Currently missing are suitable platforms capable of fast-paced high-content imaging of organoids. To address this knowledge gap, we present the OrganoidChip, a microfluidic imaging platform that incorporates a unique design to immobilize organoids for endpoint, fast imaging. The chip contains six parallel trapping areas, each having a staging and immobilization chamber, that receives organoids transferred from their native culture plates and anchors them, respectively. We first demonstrate that the OrganoidChip can efficiently immobilize intestinal and cardiac organoids without compromising their viability and functionality. Next, we show the capability of our device in assessing the dose-dependent responses of organoids’ viability and spontaneous contraction properties to Doxorubicin treatment and obtaining results that are similar to off-chip experiments. Importantly, the chip enables organoid imaging at speeds that are an order of magnitude faster than conventional imaging platforms and prevents the acquisition of blurry images caused by organoid drifting, swimming, and fast stage movements. Taken together, the OrganoidChip is a promising microfluidic platform that can serve as a building block for a multiwell plate format that can provide high-throughput and high-resolution imaging of organoids in the future.

Low-Cost Three-Dimensionally Printed Inverted Plug and Play Optical Instrument for Microfluidic Imaging

Microfluidics, also known as lab-on-a-chip or micro total analysis systems, can precisely regulate and manipulate micro-sized fluids. They have great potential in biology, chemistry, and medicine, as well as other fields of science. By definition, microfluidic devices operate with small-volume samples and small reactant quantities, which renders them both efficient and affordable. However, such small objects have very demanding requirements for the utilized optical detection system. Due to the specifics of those devices, monitoring the results of experiments is carried out with commercial inverted optical microscopes. Unfortunately, that type of optical device is still expensive. In this article, we present a truly functional, inexpensive, standalone, three-dimensionally printed, and inverted microscope, including the design, engineering, and manufacturing process and some of the experiments that have been conducted with it. Finally, we summarize the advantages of this three-dimensionally printed microscope (including the total fabrication costs) and the future improvements that will be introduced to it.

Accelerating intelligent microfluidic image processing with transfer deep learning: A microchannel droplet/bubble breakup case study

Deep learning has recently been leveraged in the microfluidic research for intelligent image processing. However, it usually requires massive human efforts to label sufficient images for obtaining a precise deep learning model. We herein propose an integrated microfluidic image processing method based on transfer deep learning for the rapid deployment of Mask R-CNN, which is capable of reutilizing models trained in previous microfluidic domains to accelerate the analysis of droplets and bubbles in the images of the target microfluidic domain. The transfer deep learning is validated in the microfluidic research with a constrictive microchannel, which is commonly used to break large droplets or bubbles to enhance emulsification. With only 40 labeled images and about 10 min training, the integrated image processing method achieves precise recognition results for both droplets and bubbles in the microfluidic experiments. Applying the trained Mask R-CNN to unlabeled images, the breakup of droplets is found to be highly dependent on the low flow rate, but the bubble breakup is much easier to happen in the same microfluidic equipment. Critical conditions of droplet breakup and size laws of droplet and bubble are precisely determined based on the recognition results of the trained Mask R-CNN.

One-channel time reversal focusing of ultra-high frequency acoustic waves on a MEMS

This Letter reports on a work performed to fabricate and characterize a silicon micro-machined cavity dedicated to micro-resolution Ultra-High Frequency imaging in microfluidics and microbiological applications using one-channel time reversal. Time reversal provides the means to spatially and temporally localize elastic energy on a receiver. Here, the arrays of zinc oxide micro transducers are coupled with a 400 μm thick silicon wafer containing micromachined structures for acoustical field confinement. Characterization of the diffused acoustic field and time-reversal retro-focusing are reported. The transducers are wideband in the 0.2–2 GHz range with a central frequency of 0.9 GHz.

Real-time intelligent classification of COVID-19 and thrombosis via massive image-based analysis of platelet aggregates.

Microvascular thrombosis is a typical symptom of COVID-19 and shows similarities to thrombosis. Using a microfluidic imaging flow cytometer, we measured the blood of 181 COVID-19 samples and 101 non-COVID-19 thrombosis samples, resulting in a total of 6.3 million bright-field images. We trained a convolutional neural network to distinguish single platelets, platelet aggregates, and white blood cells and performed classical image analysis for each subpopulation individually. Based on derived single-cell features for each population, we trained machine learning models for classification between COVID-19 and non-COVID-19 thrombosis, resulting in a patient testing accuracy of 75%. This result indicates that platelet formation differs between COVID-19 and non-COVID-19 thrombosis. All analysis steps were optimized for efficiency and implemented in an easy-to-use plugin for the image viewer napari, allowing the entire analysis to be performed within seconds on mid-range computers, which could be used for real-time diagnosis.

Dynamic nano-imaging via a microsphere compound lens integrated microfluidic device with a 10× objective lens.

Optical microscopic imaging techniques are essential in biology and chemistry fields to observe and extract dynamic information of micro/nano-scale samples in microfluidic devices. However, the current microfluidic optical imaging schemes encounter dilemmas in simultaneously possessing high spatial and temporal resolutions. Recently, microsphere nanoscope has emerged as a competitive nano-imaging tool due to its merits like high spatial resolution, real-time imaging abilities, and cost-effectiveness, which make it a potential solution to address the aforementioned challenges. Here, a microsphere compound lens (MCL) integrated microfluidic imaging device is proposed for real-time super-resolution imaging. The MCL consists of two vertically stacked microspheres, which can resolve nano-objects with size beyond the optical diffraction limit and generate an image of the object with a magnification up to 10×. Exploiting the extraordinary nano-imaging and magnification ability of the MCL, optically transparent 100 nm polystyrene particles in flowing fluid can be discerned in real time by the microfluidic device under a 10× objective lens. Contrary to this, the single microsphere and the conventional optical microscope are incompetent in this case regardless of the magnification of objective lenses used, which demonstrates the superiority of the MCL imaging scheme. Besides, applications of the microfluidic device in nanoparticle tracing and live-cell monitoring are also experimentally demonstrated. The MCL integrated microfluidic imaging device can thus be a competent technique for diverse biology and chemistry applications.

Fabrication of a paper-based facile and low-cost microfluidic device and digital imaging technique for point-of-need monitoring of hypochlorite.

Lab-on-a-paper-based devices are promising alternatives to the existing arduous techniques for point-of-need monitoring. The present work reports an instant and facile method to produce a microfluidic paper-based analytical device (μPAD). The fabricated μPAD has been used to detect hypochlorite (OCl-) by incorporating newly synthesized chromo-fluorogenic ratiometric probes 1 and 2 into the sample reception zone. The probes showed high selectivity and fast response (<10 s) toward OCl- with an excellent linear relationship in the concentration range of 0-100 μM. The concentration-dependent fluorometric change driven by the reaction of 1@μPAD with OCl- has been monitored using gel-doc imaging systems, which is unprecedented. Digitizing the intensity of the colour solution with different mathematical models of colour has developed a straightforward method for monitoring OCl- without any interference from its competitors. 1@μPAD can detect OCl- at ∼10 times lower than the WHO recommended limit. The detection limit of 1@μPAD via a digital camera-based fluorescence technique was found to be better over digital camera-based cuvette assays. Therefore, 1@μPAD has been successfully utilized to monitor OCl- in actual environmental water samples with portability, ease of use, and sensitivity. The analytical RSD was found to be ≤3% based on fluorimetric detection using 1@μPAD. The chemodosimetric reaction between OCl- and the probe was evidenced by UV-vis and fluorescence spectroscopy, 1H NMR, and ESI-MS. The rapid response time, biocompatibility, low cytotoxicity, 100% aqueous solubility, ratiometric feature, and exclusive OCl- selectivity over other competitive ROS/RNS successfully lead to the application of the probes for bioimaging of exogenous as well as endogenous OCl- in normal cells (HEK293) and cancerous cells (HeLa).

Real-time imaging of nanobubble ultrasound contrast agent flow, extravasation, and diffusion through an extracellular matrix using a microfluidic model.

Lipid shell-stabilized nanoparticles with a perfluorocarbon gas-core, or nanobubbles, have recently attracted attention as a new contrast agent for molecular ultrasound imaging and image-guided therapy. Due to their small size (∼275 nm diameter) and flexible shell, nanobubbles have been shown to extravasate through hyperpermeable vasculature (e.g., in tumors). However, little is known about the dynamics and depth of extravasation of intact, acoustically active nanobubbles. Accordingly, in this work, we developed a microfluidic chip with a lumen and extracellular matrix (ECM) and imaging method that allows real-time imaging and characterization of the extravasation process with high-frequency ultrasound. The microfluidic device has a lumen and is surrounded by an extracellular matrix with tunable porosity. The combination of ultrasound imaging and the microfluidic chip advantageously produces real-time images of the entire length and depth of the matrix. This captures the matrix heterogeneity, offering advantages over other imaging techniques with smaller fields of view. Results from this study show that nanobubbles diffuse through a 1.3 μm pore size (2 mg mL-1) collagen I matrix 25× faster with a penetration depth that was 0.19 mm deeper than a 3.7 μm (4 mg mL-1) matrix. In the 3.7 μm pore size matrix, nanobubbles diffused 92× faster than large nanobubbles (∼875 nm diameter). Decorrelation time analysis was successfully used to differentiate flowing and extra-luminally diffusing nanobubbles. In this work, we show for the first time that combination of an ultrasound-capable microfluidic chip and real-time imaging provided valuable insight into spatiotemporal nanoparticle movement through a heterogeneous extracellular matrix. This work could help accurately predict parameters (e.g., injection dosage) that improve translation of nanoparticles from in vitro to in vivo environments.