Wei Li’s research while affiliated with Texas Tech University and other places

Microfluidic devices (MDs) present a novel method for detecting circulating tumor cells (CTCs), enhancing the process through targeted techniques and visual inspection. However, current approaches often yield heterogeneous CTC populations, necessitating additional processing for comprehensive analysis and phenotype identification. These procedures are often expensive, time‐consuming, and need to be performed by skilled technicians. In this study, we investigate the potential of a cost‐effective and efficient hyperuniform micropost MD approach for CTC classification. Our approach combines mathematical modeling of fluid–structure interactions in a simulated microfluidic channel with machine learning techniques. Specifically, we developed a cell‐based modeling framework to assess CTC dynamics in erythrocyte‐laden plasma flow, generating a large dataset of CTC trajectories that account for two distinct CTC phenotypes. Convolutional neural network (CNN) and recurrent neural network (RNN) were then employed to analyze the dataset and classify these phenotypes. The results demonstrate the potential effectiveness of the hyperuniform micropost MD design and analysis approach in distinguishing between different CTC phenotypes based on cell trajectory, offering a promising avenue for early cancer detection.

Timely isolation, recovery, and identification of Salmonella from food samples is essential for prevention and control of foodborne Salmonella outbreaks. Traditional culture-based Salmonella isolation and serotyping techniques are time consuming and labor intensive. Despite the progress of innovative microfluidic or immunomagnetic isolation techniques, sophisticated lab equipment and microfabrication are often needed. Here, we present a novel, rapid yet simple method for isolation and recovery of Salmonella from mixed bacterial populations in food matrices and blood. This method utilizes self-floating hollow glass microspheres (HGMS) coated with biodegradable layer-by-layer (LbL) films and Salmonella specific antibodies. The isolation and recovery process can be completed in less than 2 h, without any sophisticated laboratory equipment or external force. In this study, we demonstrate that Salmonella can be captured due to antigen-antibody interactions on the surface of HGMS, allowing them to float to the top. The HGMS can then be washed and subjected to enzymatic degradation of the LbL film to recover the captured bacteria. The recovered Salmonella can subsequently be grown on selective agar plates for further analysis. Recovery efficiency of up to 22 % and detection limit of 100 CFU/mL were achieved. This method is expected to provide a viable alternative to traditional isolation techniques, especially in resource limited areas.

This paper explores the application of machine learning techniques to classify circulating tumor cells (CTCs) based on their trajectories within a hyperuniform micropost microfluidic device. Leveraging cell-based model-ing, we generated a synthetic dataset simulating the dynamics of CTCs in blood flow. Three machine learning architectures were applied to analyze the trajectory data: a Convolutional Neural Network (CNN), a hybrid model combining CNNs with long short-term memory (LSTM) networks, and the eXtreme Gradient Boosting (XGBoost) algorithm. These models achieved an average classification accuracy of 80% in distinguishing between different CTC phenotypes, highlighting the potential of this approach for early cancer detection. All code implementations are available as open source at: https://github.com/imsanjoykb/Microfluidic-Device-Data-CTC_Model.git.

Magnetic composite polymers combine the properties of both magnet and polymers which enable them to produce complex shape magnetic components. These materials have potential applications ranging microfluidics, vibration dampers, actuators, and minimally invasive medical devices, because when magnetic fields are applied to them, they can change shape precisely, quickly, and consistently. Our study investigates the behavior of strontium ferrite particles [SrO(Fe2O3)6] suspended in polydimethylsiloxane (PDMS) under the influence of gravity, applied magnetic fields, and time dependent behavior at different temperatures. We found that curing the PDMS and strontium ferrite suspension without a magnetic field result in a well-distributed particle arrangement with no coagulation. However, the particles align along the magnetic field lines while curing in the presence of a magnetic field (Hallback Cylinder), leaving a clear PDMS layer on top, while there is very little sedimentation due to gravity. To check this, we fabricated a 40 mm long sample and conducted hysteresis measurements in vibrating sample magnetometer (VSM) at various positions, showing minimal variation in magnetic saturation (Ms) values. Furthermore, we found a time-dependent curve of the transient angle as a function of temperature change, where the angle decreased over time as the particle’s magnetic moments aligned with the direction of the magnetic field. At lower temperatures, the transient angle decreased sharply due to lower dynamic viscosity in the uncured specimen. Hysteresis analysis and time-dependent studies at varying temperatures showed a notable change in curing that occurs at ∼55 °C, indicating the transition from a magneto-rheological fluid to a magnetorheological elastomer. The packing fraction of strontium ferrite particles and saturation magnetization were correlated, while coercivity was field-angle independent and remanence was field angle dependent.

Heterogeneities among tumor cells significantly contribute towards cancer progression and therapeutic inefficiency. Hence, understanding the nature of cancer through liquid biopsies and isolation of circulating tumor cells (CTCs) has gained considerable interest over the years. Microfluidics has emerged as one of the most popular platforms for performing liquid biopsy applications. Various label-free and labeling techniques using microfluidic platforms have been developed, the majority of which focus on CTC isolation from normal blood cells. However, sorting and profiling of various cell phenotypes present amongst those CTCs is equally important for prognostics and development of personalized therapies. In this review, firstly, we discuss the biophysical and biochemical heterogeneities associated with tumor cells and CTCs which contribute to cancer progression. Moreover, we discuss the recently developed microfluidic platforms for sorting and profiling of tumor cells and CTCs. These techniques are broadly classified into biophysical and biochemical phenotyping methods. Biophysical methods are further classified into mechanical and electrical phenotyping. While biochemical techniques have been categorized into surface antigen expressions, metabolism, and chemotaxis-based phenotyping methods. We also shed light on clinical studies performed with these platforms over the years and conclude with an outlook for the future development in this field.

Agronomic biofortification of vitamin C is a promising strategy to address vitamin C deficiencies in populations that lack access to diverse and nutritious diets. Different application methods can improve the vitamin C content in various crops; however, foliar application of ascorbic acid (AA) solutions has been under-explored. To determine if spray concentration, number of applications, and day of harvest would affect vitamin C in arugula leafy greens, foliar sprays consisting of 100 ppm and 200 ppm of AA and deionized (DI) water control were applied. Treatment application was initiated during the baby-leaf stage and subjected to a total of three sprays over the course of the experiment, followed by harvest at two days and four days after spraying (DAS). The harvested plants were measured for fresh and dry biomass and analyzed for vitamin C content, mineral composition, chlorophyll levels, and carotenoid content. The results of this study demonstrated a notably elevated total vitamin C concentration (p = 0.0002) and AA content (p = 0.02) in arugula leaves treated with a 200 ppm AA spray following the third application and harvested at 4 DAS. Additionally, the AA application improved the fresh and dry weight of leafy greens but did not exhibit any significant variances regarding the mineral composition of P, K, Ca, Mg, S, B, Zn, Mn, and Fe. Alternatively, AA foliar sprays reduced Cu content in leaves suggesting that AA reduced Cu accumulation in arugula leafy greens. In summary, the findings of this study establish that the foliar application of 200 ppm AA is an effective approach for increasing the vitamin C content in arugula leafy greens while improving the plant’s biomass, mineral composition, and stress responses. These biofortified arugula leafy greens exhibit the potential to offer plant protection against environmental stresses and a more consistent supply of vitamin C to humans upon consumption.

Microfluidic devices (MDs) present a novel method for detecting circulating tumor cells (CTCs), enhancing the process through targeted techniques and visual inspection. However, current approaches often yield heterogeneous CTC populations, necessitating additional processing for comprehensive analysis and phenotype identification. These procedures are often expensive, time-consuming, and need to be performed by skilled technicians. In this study, we investigate the potential of a cost-effective and efficient hyperuniform micropost MD approach for CTC classification. Our approach combines mathematical modeling of fluid-structure interactions in a simulated microfluidic channel with machine learning techniques. Specifically, we developed a cell-based modeling framework to assess CTC dynamics in erythrocyte-laden plasma flow, generating a large dataset of CTC trajectories that account for two distinct CTC phenotypes. Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) were then employed to analyze the dataset and classify these phenotypes. The results demonstrate the potential effectiveness of the hyperuniform micropost MD design and analysis approach in distinguishing between different CTC phenotypes based on cell trajectory, offering a promising avenue for early cancer detection.

To further investigate the inhibition of Pseudomonas aeruginosa’s in vitro growth and biofilm formation by an organo-selenium-incorporated polyurethane (PU) catheter material. P. aeruginosa, Staphylococcus aureus, and Candida albicans were incubated in vitro with organo-selenium and control polyurethane catheter materials in the presence of glutathione. Growth was evaluated by a colony-forming-unit (CFU) count and visualized with confocal laser scanning microscopy. Two different PU catheter materials were used. Using tin-catalyzed PU catheter material, complete inhibition of S. aureus was seen at 1% selenium (Se), whereas no inhibition was seen for P. aeruginosa at up to 3.0% Se. Whereas, using a thermoplastic PU catheter material, 1.5% Se and 2% Se organo-selenium caused several logs of growth inhibition of P. aeruginosa, and 2.5% selenium, incorporation showed complete inhibition (8 logs). Samples with lower than 1.5% selenium did not show adequate growth inhibition for P. aeruginosa. Similar in vitro growth inhibition was achieved against a multidrug-resistant C. albicans strain. It was concluded that optimal inhibition of P. aeruginosa in vitro growth and biofilm formation occurs with 2.5% selenium incorporated as organo-selenium in a thermoplastic PU catheter material. These results suggest that reduced incidence of CAUTIs (catheter associated urinary tract infections) with P. aeruginosa and other bacteria and fungi can be achieved by using organo-selenium-incorporated catheters.

Microfluidics have been widely used for cell sorting and capture. In this work, numerical simulations of cell transport in microfluidic devices were studied considering cell sizes, deformability, and five different device designs. Among these five designs, deterministic lateral displacement device (DLD) and hyperuniform device (HU) performed better in promoting cell-micropost collision due to the continuously shifted micropost positions as compared with regular grid, staggered, and hexagonal layout designs. However, the grid and the hexagonal layouts showed best in differentiating cells by their size dependent velocity due to the size exclusion effect for cell transport in clear and straight paths in the flow direction. A systematic study of the velocity differentiation under different dimensionless groups was performed showing that the velocity difference is dominated by the micropost separation distance perpendicular to the direction of flow. Microfluidic experiments also confirmed the velocity differentiation results. The study can provide guiding principles for microfluidic design.