Controlled incremental filtration: a simplified approach to design and fabrication of high-throughput microfluidic devices for selective enrichment of particles.

The number of microfluidic strategies aimed at separating particles or cells of a specific size within a continuous flow system continues to grow. The wide array of biomedical and other applications that would benefit from successful development of such technology has motivated the extensive research in this area over the past 15 years. However, despite promising advancements in microfabrication capabilities, a versatile approach that is suitable for a large range of particle sizes and high levels of enrichment, with a volumetric throughput sufficient for large-scale applications, has yet to emerge. Here we describe a straightforward method that enables the rapid design of microfluidic devices that are capable of enriching/removing particles within a complex aqueous mixture, with an unprecedented range of potential cutoff diameter (below 1µm to above 100µm) and an easily scalable degree of enrichment/filtration (up to 10-fold and well beyond). A simplified model of a new approach to crossflow filtration – controlled incremental filtration – was developed and validated for its ability to generate microfluidic devices that efficiently separate particles on the order of 1–10µm, with throughputs of tens of µL/min, without the use of a pump. Precise control of the amount of fluid incrementally diverted at each filtration “gap” of the device allows for the gap size (~20µm) to be much larger than the particles of interest, while the simplicity of the model allows for many thousands of these filtration points to be readily incorporated into a desired device design. This new approach should enable truly high-throughput microfluidic particle-separation devices to be generated, even by users only minimally experienced in fluid mechanics and microfabrication techniques

The relationship between red blood cell deformability metrics and perfusion of an artificial microvascular network

The ability of red blood cells (RBC) to undergo a wide range of deformations while traversing the microvasculature is crucial for adequate perfusion. Interpretation of RBC deformability measurements performed in vitro in the context of microvascular perfusion has been notoriously difficult. This study compares the measurements of RBC deformability performed using micropore filtration and ektacytometry with the RBC ability to perfuse an artificial microvascular network (AMVN). Human RBCs were collected from healthy consenting volunteers, leukoreduced, washed and exposed to graded concentrations (0% – 0.08%) of glutaraldehyde (a non-specific protein cross-linker) and diamide (a spectrin-specific protein cross-linker) to impair the deformability of RBCs. Samples comprising cells with two different levels of deformability were created by adding non-deformable RBCs (hardened by exposure to 0.08% glutaraldehyde) to the sample of normal healthy RBCs. Ektacytometry indicated a nearly linear decline in RBC deformability with increasing glutaraldehyde concentration. Micropore filtration showed a significant reduction only for concentrations of glutaraldehyde higher than 0.04%. Neither micropore filtration nor ektacytometry measurements could accurately predict the AMVN perfusion. Treatment with diamide reduced RBC deformability as indicated by ektacytometry, but had no significant effect on either micropore filtration or the AMVN perfusion. Both micropore filtration and ektacytometry showed a linear decline in effective RBC deformability with increasing fraction of non-deformable RBCs in the sample. The corresponding decline in the AMVN perfusion plateaued above 50%, reflecting the innate ability of blood flow in the microvasculature to bypass occluded capillaries. Our results suggest that in vitro measurements of RBC deformability performed using either micropore filtration or ektacytometry may not represent the ability of same RBCs to perfuse microvascular networks. Further development of biomimetic tools for measuring RBC deformability (e.g. the AMVN) could enable a more functionally relevant testing of RBC mechanical properties

Validation of a Low-Cost Paper-Based Screening Test for Sickle Cell Anemia

The high childhood mortality and life-long complications associated with sickle cell anemia (SCA) in developing countries could be significantly reduced with effective prophylaxis and education if SCA is diagnosed early in life. However, conventional laboratory methods used for diagnosing SCA remain prohibitively expensive and impractical in this setting. This study describes the clinical validation of a low-cost paper-based test for SCA that can accurately identify sickle trait carriers (HbAS) and individuals with SCA (HbSS) among adults and children over 1 year of age

Diagnosis of other forms of sickle cell disease.

<p>(<b>a</b>) Representative images of blood stains produced in paper by HbSC samples and by HbAS samples, for comparison. (<b>b</b>) Representative images of blood stains produced in paper by HbSβ⁺-thalassemia samples and by HbSS samples, for comparison. (<b>c</b>) Classification of HbSC and HbSβ⁺-thalassemia samples in the S-index domain. The values of the S-index for (○) HbAA, HbAS and HbSS samples (n = 55), (■) HbSC (n = 16) and (♦) HbSβ⁺-thalassemia (n = 3) are shown on Y-axis. The location along the X-axis of each data point for HbAS, HbSS, HbSC and HbSβ⁺-thalassemia samples corresponds to their %HbS measured with Hb electrophoresis by an off-site clinical laboratory. HbAA samples (n = 18) contained no HbS; hence the random lateral spread of the data points representing these samples on the plot.</p

Overview of the paper-based SCA diagnostic test.

<p>(<b>a</b>) To perform the test, a 20 μL droplet of blood mixed 1:10 (by volume) with Hb solubility buffer–a concentrated phosphate buffer (2.49M) containing a hemolytic (saponin) and a reducing agent (sodium hydrosulfite)–was deposited on paper. Differential transport of polymerized HbS and soluble forms of Hb in the paper substrate produced blood stains with characteristic patterns. (<b>b</b>) Representative images of the blood stain patterns produced by HbAA, HbAS and HbSS samples.</p

Validation of the paper-based SCA test in a research laboratory and in a resource-limited clinical setting (Cabinda, Angola).

<p>(<b>a</b>) Aggregate confusion matrix for the diagnoses of blood samples collected from normal volunteers and patients of Pediatric Hematology-Oncology Clinic at Tulane University Hospital and of the Sickle Cell Center of Southern Louisiana (New Orleans, LA) performed via visual evaluation of the blood stains by human scorers (n = 5). Rows correspond to true genotypes (diagnosed by hemoglobin electrophoresis) and columns correspond to predicted genotypes (diagnosed by the paper-based test). Shaded cells along the diagonal contain numbers of correct diagnoses. (<b>b</b>) Confusion matrix for the diagnoses of blood samples collected at the Primero de Maio obstetric hospital from postnatal females with unknown SCA status. The rapid test was performed and interpreted via visual evaluation by healthcare workers at the newborn screening laboratory of the Clinica de Celulas Falciformes at the Dispensario Materno Infantil (Cabinda, Angola). Rows correspond to true genotypes (diagnosed by isoelectric focusing) and columns correspond to predicted genotypes (diagnosed by the paper-based test). Shaded cells along the diagonal contain numbers of correct diagnoses.</p

Automated analysis of blood stains in paper.

<p>(<b>a</b>) A custom image analysis algorithm automatically detected the center of each blood stain (dashed crosshair) and extracted the RGB values for all pixels contained within the dark red center spot (smaller dashed circle) and within the pink peripheral ring (area between the smaller and the larger dashed circles). The S-index was defined as the quotient of the mean red color intensity of the center spot and that of the peripheral ring of the blood stain. (<b>b</b>) The values of the S-index for (●) HbAA (n = 18), (♦) HbAS (n = 17) and (■) HbSS (n = 20) samples obtained from healthy subjects and patients in New Orleans, LA. (<b>c</b>) Receiver operating characteristic (ROC) curves for the use of S-index to identify HbAA, HbAS and HbSS samples. The area under the curve (AUC) for discriminating HbAA from HbAS and HbSS was 1.00, the AUC for discriminating HbSS from HbAA and HbAS was 0.9986 and the AUC for discriminating HbSS from HbAS was 0.9971.</p