Electrical Detection of Innate Immune Cells.

Accurately classifying the innate immune players is essential to comprehensively and quantitatively evaluate the interactions between the innate and the adaptive immune systems. In addition, accurate classification enables the development of models to predict behavior and to improve prospects for therapeutic manipulation of inflammatory diseases and cancer. Rapid development in technologies that provide an accurate definition of the type of cell in action, allows the field of innate immunity to the lead in therapy developments. This article presents a novel immunophenotyping technique using electrical characterization to differentiate between the two most important cell types of the innate immune system: dendritic cells (DCs) and macrophages (MACs). The electrical characterization is based on capacitance measurements, which is a reliable marker for cell surface area and hence cell size. We differentiated THP-1 cells into DCs and MACs in vitro and conducted electrical measurements on the three cell types. The results showed average capacitance readings of 0.83 µF, 0.93 µF, and 1.01 µF for THP-1, DCs, and MACs, respectively. This corresponds to increasing cell size since capacitance is directly proportional to area. The results were verified with image processing. Image processing was used for verification because unlike conventional techniques, especially flow cytometry, it avoids cross referencing and by-passes the limitation of a lack of specificity of markers used to detect the different cell types.

Autoregressive parametric modeling combined ANOVA approach for label-free-based cancerous and normal cells discrimination.

Label free based methods received huge interest in the field of bio cell characterizations because they do not cause any cell damage nor contribute any change in its compositions. This work takes a close outlook of cancerous cells discrimination from normal cells utilizing parametric modeling approach. Autoregressive (AR) modeling technique is used to fit the measured optical transmittance profiles of both cancer and normal cells. The transmitted light intensity, when passes through the cells, gets affected by their intercellular compositions and membrane properties. In this study, four types of cells: lung-cancerous and normal, liver-cancerous and normal, were suspended in their corresponding medium and their transmission characteristics were collected and processed. The AR coefficients of each type of the cell were analyzed with the statistical technique called Analysis of variance (ANOVA), which provided the significant coefficients. The poles extracted from the significant coefficients resulted in an improved demarcation for normal and cancer cells. These outcomes can be further utilized for cell classification using statistical tools.

Simultaneous and rapid quantification of microalga biomolecule content using electrochemical impedance spectroscopy.

Lipids, proteins, and carbohydrates are the major constituents found in microalga cells, in varying proportions, and these biomolecules find applications in different industries. During microalga cultivation, to efficiently manipulate, control, and optimize the productivity of a specific compound for a specific application, real-time monitoring of these three cell components is essential. In this study, a method using measurement of electrical capacitance was developed to simultaneously determine the lipid, protein, and carbohydrate content of microalga cells without the requirement for any pre-processing steps. The marine microalga Nannochloropsis oculata was cultivated under nitrogen starvation conditions to induce lipid accumulation over a period of 22 days. The correlation between the electrical capacitance of the microalga culture and the intracellular biomolecule content (determined by standard techniques) was investigated, enabling subsequent deduction of microalga intracellular content from electrical capacitance of the culture. The accuracy and precision of the technique were proven by validating an independent sample. The main advantage of the proposed technique is its capability of quantifying microalga composition within a few minutes, significantly faster than currently available conventional techniques.

Simultaneous piezoelectric noninvasive detection of multiple vital signs.

The monitoring of vital signs plays a key role in the diagnosis of several diseases. Piezoelectric sensors have been utilized to collect a corresponding representative signal from the chest surface. The subject typically needs to hold his or her breath to eliminate the respiration effect. This work further contributes to the extraction of the corresponding representative vital signs directly from the measured respiration signal. The contraction and expansion of the heart muscles, as well as the respiration activities, will induce a mechanical vibration across the chest wall. The induced vibration is then captured by the piezoelectric sensor placed at the chest surface, which produces an electrical output voltage signal conformally mapped with the respiration-cardiac activities. During breathing, the measured voltage signal is composed of the cardiac cycle activities modulated along with the respiratory cycle activity. A representative model that incorporates the cardiac and respiratory activities is developed and adopted. The piezoelectric and the convolution theories along with Fourier transformation are applied to extract the corresponding cardiac activity signal from the respiration signal. All the results were validated step by step by a conventional apparatus, with good agreement observed.

Electrical detection of blood cells in urine.

Available methods for detecting blood in the urine (hematuria) can be problematic since results can be influenced by many factors in patients and in the lab settings, resulting in false positive or false negative results. This necessitates the development of new, accurate and easy-access methods that save time and effort. This study demonstrates a label-free and accurate method for detecting the presence of red and white blood cells (RBCs and WBCs) in urine by measuring the changes in the dielectric properties of urine upon increasing concentrations of both cell types. The current method could detect changes in the electrical properties of fresh urine over a short time interval, making this method suitable for detecting changes that cannot be recognized by conventional methods. Correcting for these changes enabled the detection of a minimum cell concentration of 102 RBCs per ml which is not possible by conventional methods used in the labs except for the semi-quantitative method that can detect 50 RBCs per ml, but it is a lengthy and involved procedure, not suitable for high volume labs. This ability to detect very small amount of both types of cells makes the proposed technique an attractive tool for detecting hematuria, the presence of which is indicative of problems in the excretory system.

Electrical extraction of piezoelectric constants.

The piezoelectric materials are incorporated in smart structure to exhibit specific functionality. The activity of piezoelectric material dimension and electrical properties can be changed with an applied stress. These variations are translated to a change in the capacitance of the structure. This work takes a close outlook on the use of the capacitance-voltage measurements for the extraction of double piezoelectric thin film material deposited at the two faces of a flexible steel sheet. The piezoelectric thin film materials have been deposited using RF sputtering techniques. Gamry analyzer references 3000 was used to collect the capacitance-voltage measurements from both layers. The developed algorithm extracts directly the piezoelectric coefficients knowing the film thickness, the applied voltage, and the capacitance ratio. The capacitance ratio is the ratio between the capacitances of the film when the applied field in antiparallel and parallel to the polling field direction, respectively. The method has been calibrated using a piezoelectric bulk ceramic and validated by comparing the result with the reported values in the literature. The extracted values using the current approach match well the values extracted by other existing methods.

Bilirubin detoxification using different phytomaterials: characterization and in vitro studies.

BACKGROUND: Activated carbon (AC) is a common adsorbent that is used in both artificial and bioartificial liver devices. METHODS: Three natural materials - date pits of Phoenix dactylifera (fruit), Simmondsia chinensis (jojoba) seeds, and Scenedesmus spp. (microalgae) - were used in the present investigation as precursors for the synthesis of AC using physical activation. The chemical structures and morphology of AC were analyzed. Then, AC's bilirubin adsorption capacity and its cytotoxicity on normal liver (THLE2) and liver cancer (HepG2) cells were characterized. RESULTS: Compared with the other raw materials examined, date-pit AC was highly selective and showed the most effective capacity of bilirubin adsorption, as judged by isotherm-modeling analysis. MTT in vitro analysis indicated that date-pit AC had the least effect on the viability of both THLE2 and HepG2 cells compared to jojoba seeds and microalgae. All three biomaterials under investigation were used, along with collagen and Matrigel, to grow cells in 3D culture. Fluorescent microscopy confirmed date-pit AC as the best to preserve liver cell integrity. CONCLUSION: The findings of this study introduce date-pit-based AC as a novel alternative biomaterial for the removal of protein-bound toxins in bioartificial liver devices.

Label-free capacitance-based identification of viruses.

This study was undertaken to quantitate a single virus suspension in culture medium without any pre-processing. The electrical capacitance per virus particle was used to identify the kind of virus present by measuring the suspension (virus plus medium) capacitance, de-embedding the medium contribution, and dividing by the virus count. The proposed technique is based on finding the single virus effective dielectric constant which is directly related to the virus composition. This value was used to identify the virus type accordingly. Two types of viruses thus tested were further quantified by a biochemical technique to validate the results. Furthermore, non-organic nanoparticles with known concentration and capacitance per particle were identified using the proposed method. The selectivity of the method was demonstrated by performing electrical measurements on a third virus, revealing that the proposed technique is specific and sensitive enough to permit detection of a few hundred virus particles per milliliter within a few minutes.

Virus detection and quantification using electrical parameters.

Here we identify and quantitate two similar viruses, human and feline immunodeficiency viruses (HIV and FIV), suspended in a liquid medium without labeling, using a semiconductor technique. The virus count was estimated by calculating the impurities inside a defined volume by observing the change in electrical parameters. Empirically, the virus count was similar to the absolute value of the ratio of the change of the virus suspension dopant concentration relative to the mock dopant over the change in virus suspension Debye volume relative to mock Debye volume. The virus type was identified by constructing a concentration-mobility relationship which is unique for each kind of virus, allowing for a fast (within minutes) and label-free virus quantification and identification. For validation, the HIV and FIV virus preparations were further quantified by a biochemical technique and the results obtained by both approaches corroborated well. We further demonstrate that the electrical technique could be applied to accurately measure and characterize silica nanoparticles that resemble the virus particles in size. Based on these results, we anticipate our present approach to be a starting point towards establishing the foundation for label-free electrical-based identification and quantification of an unlimited number of viruses and other nano-sized particles.

RF microalgal lipid content characterization.

Most conventional techniques for the determination of microalgae lipid content are time consuming and in most cases are indirect and require excessive sample preparations. This work presents a new technique that utilizes radio frequency (RF) for rapid lipid quantification, without the need for sample preparation. Tests showed that a shift in the resonance frequency of a RF open-ended coaxial resonator and a gradual increase in its resonance magnitude may occur as the lipids content of microalgae cells increases. These response parameters can be then calibrated against actual cellular lipid contents and used for rapid determination of the cellular lipids. The average duration of lipid quantification using the proposed technique was of about 1 minute, which is significantly less than all other conventional techniques, and was achieved without the need for any time consuming treatment steps.