The influence of the female reproductive tract and sperm features on the design of microfluidic sperm-sorting devices.

Although medical advancements have successfully helped a lot of couples with their infertility by assisted reproductive technologies (ART), sperm selection, a crucial stage in ART, has remained challenging. Therefore, we aimed to investigate novel sperm separation methods, specifically microfluidic systems, as they do sperm selection based on sperm and/or the female reproductive tract (FRT) features without inflicting any damage to the selected sperm during the process. In this review, after an exhaustive studying of FRT features, which can implement by microfluidics devices, the focus was centered on sperm selection and investigation devices. During this study, we tried not to only point to the deficiencies of these systems, but to put forth suggestions for their improvement as well.

Integrating deep learning with microfluidics for biophysical classification of sickle red blood cells adhered to laminin.

Sickle cell disease, a genetic disorder affecting a sizeable global demographic, manifests in sickle red blood cells (sRBCs) with altered shape and biomechanics. sRBCs show heightened adhesive interactions with inflamed endothelium, triggering painful vascular occlusion events. Numerous studies employ microfluidic-assay-based monitoring tools to quantify characteristics of adhered sRBCs from high resolution channel images. The current image analysis workflow relies on detailed morphological characterization and cell counting by a specially trained worker. This is time and labor intensive, and prone to user bias artifacts. Here we establish a morphology based classification scheme to identify two naturally arising sRBC subpopulations-deformable and non-deformable sRBCs-utilizing novel visual markers that link to underlying cell biomechanical properties and hold promise for clinically relevant insights. We then set up a standardized, reproducible, and fully automated image analysis workflow designed to carry out this classification. This relies on a two part deep neural network architecture that works in tandem for segmentation of channel images and classification of adhered cells into subtypes. Network training utilized an extensive data set of images generated by the SCD BioChip, a microfluidic assay which injects clinical whole blood samples into protein-functionalized microchannels, mimicking physiological conditions in the microvasculature. Here we carried out the assay with the sub-endothelial protein laminin. The machine learning approach segmented the resulting channel images with 99.1±0.3% mean IoU on the validation set across 5 k-folds, classified detected sRBCs with 96.0±0.3% mean accuracy on the validation set across 5 k-folds, and matched trained personnel in overall characterization of whole channel images with R2 = 0.992, 0.987 and 0.834 for total, deformable and non-deformable sRBC counts respectively. Average analysis time per channel image was also improved by two orders of magnitude (∼ 2 minutes vs ∼ 2-3 hours) over manual characterization. Finally, the network results show an order of magnitude less variance in counts on repeat trials than humans. This kind of standardization is a prerequisite for the viability of any diagnostic technology, making our system suitable for affordable and high throughput disease monitoring.

Identification of fetal aneuploidy with dual-probe fluorescence in situ hybridization analysis in circulating trophoblasts after enrichment using a high-sensitivity microfluidic platform.

OBJECTIVE: To evaluate a microfluidics-based positive selection technology for isolating circulating trophoblasts (CTs) from peripheral blood of women whose pregnancies are affected by aneuploidy and to evaluate fetal karyotype using fluorescence in situ hybridization (FISH). METHOD: Ten 18-ml samples of peripheral blood were collected consecutively from pregnant women whose fetus was affected by aneuploidy. A preservation buffer was added, and the specimens were shipped overnight to the testing laboratory at ambient temperature. The specimen was infused into the fully automated microfluidics-based LiquidScan® instrument without pre-processing. This instrument contains microfluidic chips, which are coated with antibodies (anti-huEpCAM and a proprietary antibody mixture) specific to CT surface epitopes. FISH analysis was performed on the enriched cells. RESULTS: Fetal aneuploidy evaluated included trisomy 21 (n = 3), trisomy 18 (n = 1), trisomy 13 (n = 1), monosomy X (n = 3), and triploidy (n = 1). CTs for analysis by FISH were identified in all samples. The average number of mononucleate cells per 1 ml of whole blood was 2.11 (range 0.38-4.63) overall and was 2.67 (range 1.13-4.63) using the proprietary combination of antibodies. FISH results were concordant with the aneuploidy based on other testing in all cases. Multinucleate cells were searched for and identified in the last seven samples (average number: 0.84/1 ml). CONCLUSIONS: Our study demonstrates that the LiquidScan® , a high-sensitivity microfluidic platform, can enrich circulating trophoblasts (mononucleate and multinucleate). FISH can then be used to detect fetal aneuploidy.

Mathematical modelling of pressure-driven micropolar biological flow due to metachronal wave propulsion of beating cilia.

In this paper, we present an analytical study of pressure-driven flow of micropolar non-Newtonian physiological fluids through a channel comprising two parallel oscillating walls. The cilia are arranged at equal intervals and protrude normally from both walls of the infinitely long channel. A metachronal wave is generated due to natural beating of cilia and the direction of wave propagation is parallel to the direction of fluid flow. Appropriate expressions are presented for deformation via longitudinal and transverse velocity components induced by the ciliary beating phenomenon with cilia assumed to follow elliptic trajectories. The conservation equations for mass, longitudinal and transverse (linear) momentum and angular momentum are reduced in accordance with the long wavelength and creeping Stokesian flow approximations and then normalized with appropriate transformations. The resulting non-linear moving boundary value problem is solved analytically for constant micro-inertia density, subject to physically realistic boundary conditions. Closed-form expressions are derived for axial velocity, angular velocity, volumetric flow rate and pressure rise. The transport phenomena are shown to be dictated by several non-Newtonian parameters, including micropolar material parameter and Eringen coupling parameter, and also several geometric parameters, viz eccentricity parameter, wave number and cilia length. The influence of these parameters on streamline profiles (with a view to addressing trapping features via bolus formation and evolution), pressure gradient and other characteristics are evaluated graphically. Both axial and angular velocities are observed to be substantially modified with both micropolar rheological parameters and furthermore are significantly altered with increasing volumetric flow rate. Free pumping is also examined. An inverse relationship between pressure rise and flow rate is computed which is similar to that observed in Newtonian fluids. The study is relevant to hemodynamics in narrow capillaries and also bio-inspired micro-fluidic devices.

Wound-induced Ca2+ wave propagates through a simple release and diffusion mechanism.

Damage-associated molecular patterns (DAMPs) are critical mediators of information concerning tissue damage from damaged cells to neighboring healthy cells. ATP acts as an effective DAMP when released into extracellular space from damaged cells. Extracellular ATP receptors monitor tissue damage and activate a Ca2+ wave in the surrounding healthy cells. How the Ca2+ wave propagates through cells after a wound is unclear. Ca2+ wave activation can occur extracellularly via external receptors or intracellularly through GAP junctions. Three potential mechanisms to propagate the Ca2+ wave are source and sink, amplifying wave, and release and diffusion. Both source and sink and amplifying wave regulate ATP levels using hydrolysis or secretion, respectively, whereas release and diffusion relies on dilution. Here we systematically test these hypotheses using a microfluidics assay to mechanically wound an epithelial monolayer in combination with direct manipulation of ATP hydrolysis and release. We show that a release and diffusion model sufficiently explains Ca2+-wave propagation after an epithelial wound. A release and diffusion model combines the benefits of fast activation at short length scales with a self-limiting response to prevent unnecessary inflammatory responses harmful to the organism.

High-throughput manufacturing of size-tuned liposomes by a new microfluidics method using enhanced statistical tools for characterization.

Microfluidics has recently emerged as a new method of manufacturing liposomes, which allows for reproducible mixing in miliseconds on the nanoliter scale. Here we investigate microfluidics-based manufacturing of liposomes. The aim of these studies was to assess the parameters in a microfluidic process by varying the total flow rate (TFR) and the flow rate ratio (FRR) of the solvent and aqueous phases. Design of experiment and multivariate data analysis were used for increased process understanding and development of predictive and correlative models. High FRR lead to the bottom-up synthesis of liposomes, with a strong correlation with vesicle size, demonstrating the ability to in-process control liposomes size; the resulting liposome size correlated with the FRR in the microfluidics process, with liposomes of 50 nm being reproducibly manufactured. Furthermore, we demonstrate the potential of a high throughput manufacturing of liposomes using microfluidics with a four-fold increase in the volumetric flow rate, maintaining liposome characteristics. The efficacy of these liposomes was demonstrated in transfection studies and was modelled using predictive modeling. Mathematical modelling identified FRR as the key variable in the microfluidic process, with the highest impact on liposome size, polydispersity and transfection efficiency. This study demonstrates microfluidics as a robust and high-throughput method for the scalable and highly reproducible manufacture of size-controlled liposomes. Furthermore, the application of statistically based process control increases understanding and allows for the generation of a design-space for controlled particle characteristics.

The present and future role of microfluidics in biomedical research.

Microfluidics, a technology characterized by the engineered manipulation of fluids at the submillimetre scale, has shown considerable promise for improving diagnostics and biology research. Certain properties of microfluidic technologies, such as rapid sample processing and the precise control of fluids in an assay, have made them attractive candidates to replace traditional experimental approaches. Here we analyse the progress made by lab-on-a-chip microtechnologies in recent years, and discuss the clinical and research areas in which they have made the greatest impact. We also suggest directions that biologists, engineers and clinicians can take to help this technology live up to its potential.

Compressed sensing of remotely detected MRI velocimetry in microfluidics.

NMR and MRI can yield detailed chemical and dynamic information about flow at microscopic resolutions, but suffer from low signal to noise relative to alternative techniques for flow measurements. In porous media and microfluidic devices, this sensitivity problem is further exacerbated by magnetic susceptibility broadening and low coil filling factor. Fortunately, remote detection can mitigate these issues by physically separating signal detection from the other steps of the experiment. The technique requires, however, that any measured interactions be encoded in indirectly sampled dimensions, leading to experiments of high dimensionality and correspondingly long acquisition times. We have applied compressed sensing, a reconstruction technique used in MRI, to dramatically reduce these experiment times by 8-64x through partial sampling (sub-sampling) of k-space, allowing for the collection of images with significantly higher resolutions in reasonable amounts of time. Here, we demonstrate this reconstruction technique to remotely detected flow measurements in a serpentine mixing chip and in a microfluidic channel harboring a constriction. We find that compressed sensing allows for significantly higher resolution images to be collected in a practical amount of time, thus significantly enhancing the applicability of remote detection to flow imaging.

Beating Poisson encapsulation statistics using close-packed ordering.

Loading drops with discrete objects, such as particles and cells, is often necessary when performing chemical and biological assays in microfluidic devices. However, random loading techniques are inefficient, yielding a majority of empty and unusable drops. We use deformable particles that are close packed to insert a controllable number of particles into every drop. This provides a simple, flexible means of efficiently encapsulating a controllable number of particles per drop.

Influence of varying electroosmotic flow on the effective diffusion in electric field gradient separations.

Recently the use electric field gradient focusing (EFGF) to enhance focusing of proteins has been proposed and explored to provide significant improvement in separation resolution. The objective of EFGF is to focus proteins of specific electrophoretic mobilities at distinct stationary locations in a column or channel. This can be accomplished in a capillary by allowing the electric potential to vary in the streamwise direction. Because the electric field is varying, so also is the electrokinetic force exerted on the proteins and the electroosmotic velocity of the buffer solution. Due to the varying electric field, the Taylor diffusion characteristics will also vary along the column, causing a degradation of peak widths of some proteins, dependent on their equilibrium positions and local velocity distributions. The focus of this paper is an analysis that allows characterization of the local Taylor diffusion and resulting protein band peak width as a function of the local magnitude of the EOF relative to the average fluid velocity for both cylindrical and rectangular channels. In general the analysis shows that as the ratio of the local electroosmotic velocity to the average velocity deviates from unity, the effective diffusion increases significantly. The effectiveness of EFGF devices over a range of protein diffusivities, capillary diameters, flow velocities, and electric field gradient is discussed.